Core [omni.isaac.core]
Articulations
Articulation
- class Articulation(prim_path: str, name: str = 'articulation', position: Optional[Sequence[float]] = None, translation: Optional[Sequence[float]] = None, orientation: Optional[Sequence[float]] = None, scale: Optional[Sequence[float]] = None, visible: Optional[bool] = None, articulation_controller: Optional[omni.isaac.core.controllers.articulation_controller.ArticulationController] = None)
High level wrapper to deal with an articulation prim (only one articulation prim) and its attributes/properties.
Warning
The articulation object must be initialized in order to be able to operate on it. See the
initializemethod for more details.- Parameters
prim_path (str) – prim path of the Prim to encapsulate or create.
name (str, optional) – shortname to be used as a key by Scene class. Note: needs to be unique if the object is added to the Scene. Defaults to “articulation”.
position (Optional[Sequence[float]], optional) – position in the world frame of the prim. Shape is (3, ). Defaults to None, which means left unchanged.
translation (Optional[Sequence[float]], optional) – translation in the local frame of the prim (with respect to its parent prim). Shape is (3, ). Defaults to None, which means left unchanged.
orientation (Optional[Sequence[float]], optional) – quaternion orientation in the world/ local frame of the prim (depends if translation or position is specified). quaternion is scalar-first (w, x, y, z). Shape is (4, ). Defaults to None, which means left unchanged.
scale (Optional[Sequence[float]], optional) – local scale to be applied to the prim’s dimensions. Shape is (3, ). Defaults to None, which means left unchanged.
visible (bool, optional) – set to false for an invisible prim in the stage while rendering. Defaults to True.
articulation_controller (Optional[ArticulationController], optional) – a custom ArticulationController which inherits from it. Defaults to creating the basic ArticulationController.
Example:
>>> import omni.isaac.core.utils.stage as stage_utils >>> from omni.isaac.core.articulations import Articulation >>> >>> usd_path = "/home/<user>/Documents/Assets/Robots/Franka/franka_alt_fingers.usd" >>> prim_path = "/World/envs/env_0/panda" >>> >>> # load the Franka Panda robot USD file >>> stage_utils.add_reference_to_stage(usd_path, prim_path) >>> >>> # wrap the prim as an articulation >>> prim = Articulation(prim_path=prim_path, name="franka_panda") >>> prim <omni.isaac.core.articulations.articulation.Articulation object at 0x7fdd165bf520>
- apply_action(control_actions: omni.isaac.core.utils.types.ArticulationAction) None
Apply joint positions, velocities and/or efforts to control an articulation
- Parameters
control_actions (ArticulationAction) – actions to be applied for next physics step.
indices (Optional[Union[list, np.ndarray]], optional) – degree of freedom indices to apply actions to. Defaults to all degrees of freedom.
Hint
High stiffness makes the joints snap faster and harder to the desired target, and higher damping smoothes but also slows down the joint’s movement to target
For position control, set relatively high stiffness and low damping (to reduce vibrations)
For velocity control, stiffness must be set to zero with a non-zero damping
For effort control, stiffness and damping must be set to zero
Example:
>>> from omni.isaac.core.utils.types import ArticulationAction >>> >>> # move all the robot joints to the indicated position >>> action = ArticulationAction(joint_positions=np.array([0.0, -1.0, 0.0, -2.2, 0.0, 2.4, 0.8, 0.04, 0.04])) >>> prim.apply_action(action) >>> >>> # close the robot fingers: panda_finger_joint1 (7) and panda_finger_joint2 (8) to 0.0 >>> action = ArticulationAction(joint_positions=np.array([0.0, 0.0]), joint_indices=np.array([7, 8])) >>> prim.apply_action(action)
- apply_visual_material(visual_material: omni.isaac.core.materials.visual_material.VisualMaterial, weaker_than_descendants: bool = False) None
Apply visual material to the held prim and optionally its descendants.
- Parameters
visual_material (VisualMaterial) – visual material to be applied to the held prim. Currently supports PreviewSurface, OmniPBR and OmniGlass.
weaker_than_descendants (bool, optional) – True if the material shouldn’t override the descendants materials, otherwise False. Defaults to False.
Example:
>>> from omni.isaac.core.materials import OmniGlass >>> >>> # create a dark-red glass visual material >>> material = OmniGlass( ... prim_path="/World/material/glass", # path to the material prim to create ... ior=1.25, ... depth=0.001, ... thin_walled=False, ... color=np.array([0.5, 0.0, 0.0]) ... ) >>> prim.apply_visual_material(material)
- disable_gravity() None
Keep gravity from affecting the robot
Example:
>>> prim.disable_gravity()
- property dof_names: List[str]
List of prim names for each DOF.
- Returns
prim names
- Return type
list(string)
Example:
>>> prim.dof_names ['panda_joint1', 'panda_joint2', 'panda_joint3', 'panda_joint4', 'panda_joint5', 'panda_joint6', 'panda_joint7', 'panda_finger_joint1', 'panda_finger_joint2']
- property dof_properties: numpy.ndarray
Articulation DOF properties
DOF properties Index
Property name
Description
0
typeDOF type: invalid/unknown/uninitialized (0), rotation (1), translation (2)
1
hasLimitsWhether the DOF has limits
2
lowerLower DOF limit (in radians or meters)
3
upperUpper DOF limit (in radians or meters)
4
driveModeDrive mode for the DOF: force (1), acceleration (2)
5
maxVelocityMaximum DOF velocity. In radians/s, or stage_units/s
6
maxEffortMaximum DOF effort. In N or N*stage_units
7
stiffnessDOF stiffness
8
dampingDOF damping
- Returns
named NumPy array of shape (num_dof, 9)
- Return type
np.ndarray
Example:
>>> # get properties for all DOFs >>> prim.dof_properties [(1, True, -2.8973, 2.8973, 1, 1.0000000e+01, 5220., 60000., 3000.) (1, True, -1.7628, 1.7628, 1, 1.0000000e+01, 5220., 60000., 3000.) (1, True, -2.8973, 2.8973, 1, 5.9390470e+36, 5220., 60000., 3000.) (1, True, -3.0718, -0.0698, 1, 5.9390470e+36, 5220., 60000., 3000.) (1, True, -2.8973, 2.8973, 1, 5.9390470e+36, 720., 25000., 3000.) (1, True, -0.0175, 3.7525, 1, 5.9390470e+36, 720., 15000., 3000.) (1, True, -2.8973, 2.8973, 1, 1.0000000e+01, 720., 5000., 3000.) (2, True, 0. , 0.04 , 1, 3.4028235e+38, 720., 6000., 1000.) (2, True, 0. , 0.04 , 1, 3.4028235e+38, 720., 6000., 1000.)] >>> >>> # property names >>> prim.dof_properties.dtype.names ('type', 'hasLimits', 'lower', 'upper', 'driveMode', 'maxVelocity', 'maxEffort', 'stiffness', 'damping') >>> >>> # get DOF upper limits >>> prim.dof_properties["upper"] [ 2.8973 1.7628 2.8973 -0.0698 2.8973 3.7525 2.8973 0.04 0.04 ] >>> >>> # get the last DOF (panda_finger_joint2) upper limit >>> prim.dof_properties["upper"][8] # or prim.dof_properties[8][3] 0.04
- enable_gravity() None
Gravity will affect the robot
Example:
>>> prim.enable_gravity()
- get_angular_velocity() numpy.ndarray
Get the angular velocity of the root articulation prim
- Returns
3D angular velocity vector. Shape (3,)
- Return type
np.ndarray
Example:
>>> prim.get_angular_velocity() [0. 0. 0.]
- get_applied_action() omni.isaac.core.utils.types.ArticulationAction
Get the last applied action
- Returns
last applied action. Note: a dictionary is used as the object’s string representation
- Return type
Example:
>>> # last applied action: joint_positions -> [0.0, -1.0, 0.0, -2.2, 0.0, 2.4, 0.8, 0.04, 0.04] >>> prim.get_applied_action() {'joint_positions': [0.0, -1.0, 0.0, -2.200000047683716, 0.0, 2.4000000953674316, 0.800000011920929, 0.03999999910593033, 0.03999999910593033], 'joint_velocities': [0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0], 'joint_efforts': [0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0]}
- get_applied_joint_efforts(joint_indices: Optional[Union[List, numpy.ndarray]] = None) numpy.ndarray
Get the efforts applied to the joints set by the
set_joint_effortsmethod- Parameters
joint_indices (Optional[Union[List, np.ndarray]], optional) – indices to specify which joints to read. Defaults to None (all joints)
- Raises
Exception – If the handlers are not initialized
- Returns
all or selected articulation joint applied efforts
- Return type
np.ndarray
Example:
>>> # get all applied joint efforts >>> prim.get_applied_joint_efforts() [ 0. 0. 0. 0. 0. 0. 0. 0. 0.] >>> >>> # get finger applied efforts: panda_finger_joint1 (7) and panda_finger_joint2 (8) >>> prim.get_applied_joint_efforts(joint_indices=np.array([7, 8])) [0. 0.]
- get_applied_visual_material() omni.isaac.core.materials.visual_material.VisualMaterial
Return the current applied visual material in case it was applied using apply_visual_material or it’s one of the following materials that was already applied before: PreviewSurface, OmniPBR and OmniGlass.
- Returns
the current applied visual material if its type is currently supported.
- Return type
Example:
>>> # given a visual material applied >>> prim.get_applied_visual_material() <omni.isaac.core.materials.omni_glass.OmniGlass object at 0x7f36263106a0>
- get_articulation_body_count() int
Get the number of bodies (links) that make up the articulation
- Returns
amount of bodies
- Return type
int
Example:
>>> prim.get_articulation_body_count() 12
- get_articulation_controller() omni.isaac.core.controllers.articulation_controller.ArticulationController
Get the articulation controller
Note
If no
articulation_controllerwas passed during class instantiation, a default controller of typeArticulationController(a Proportional-Derivative controller that can apply position targets, velocity targets and efforts) will be used- Returns
articulation controller
- Return type
Example:
>>> prim.get_articulation_controller() <omni.isaac.core.controllers.articulation_controller.ArticulationController object at 0x7f04a0060190>
- get_default_state() omni.isaac.core.utils.types.XFormPrimState
Get the default prim states (spatial position and orientation).
- Returns
an object that contains the default state of the prim (position and orientation)
- Return type
Example:
>>> state = prim.get_default_state() >>> state <omni.isaac.core.utils.types.XFormPrimState object at 0x7f33addda650> >>> >>> state.position [-4.5299529e-08 -1.8347054e-09 -2.8610229e-08] >>> state.orientation [1. 0. 0. 0.]
- get_dof_index(dof_name: str) int
Get a DOF index given its name
- Parameters
dof_name (str) – name of the DOF
- Returns
DOF index
- Return type
int
Example:
>>> prim.get_dof_index("panda_finger_joint2") 8
- get_enabled_self_collisions() int
Get the enable self collisions flag (
physxArticulation:enabledSelfCollisions)- Returns
self collisions flag (boolean interpreted as int)
- Return type
int
Example:
>>> prim.get_enabled_self_collisions() 0
- get_joint_positions(joint_indices: Optional[Union[List, numpy.ndarray]] = None) numpy.ndarray
Get the articulation joint positions
- Parameters
joint_indices (Optional[Union[List, np.ndarray]], optional) – indices to specify which joints to read. Defaults to None (all joints)
- Returns
all or selected articulation joint positions
- Return type
np.ndarray
Example:
>>> # get all joint positions >>> prim.get_joint_positions() [ 1.1999920e-02 -5.6962633e-01 1.3480479e-08 -2.8105433e+00 6.8284894e-06 3.0301569e+00 7.3234749e-01 3.9912373e-02 3.9999999e-02] >>> >>> # get finger positions: panda_finger_joint1 (7) and panda_finger_joint2 (8) >>> prim.get_joint_positions(joint_indices=np.array([7, 8])) [0.03991237 3.9999999e-02]
- get_joint_velocities(joint_indices: Optional[Union[List, numpy.ndarray]] = None) numpy.ndarray
Get the articulation joint velocities
- Parameters
joint_indices (Optional[Union[List, np.ndarray]], optional) – indices to specify which joints to read. Defaults to None (all joints)
- Returns
all or selected articulation joint velocities
- Return type
np.ndarray
Example:
>>> # get all joint velocities >>> prim.get_joint_velocities() [ 1.91603772e-06 -7.67638255e-03 -2.19138826e-07 1.10636465e-02 -4.63412944e-05 3.48245539e-02 8.84692147e-02 5.40335372e-04 1.02849208e-05] >>> >>> # get finger velocities: panda_finger_joint1 (7) and panda_finger_joint2 (8) >>> prim.get_joint_velocities(joint_indices=np.array([7, 8])) [5.4033537e-04 1.0284921e-05]
- get_joints_default_state() omni.isaac.core.utils.types.JointsState
Get the default joint states (positions and velocities).
- Returns
an object that contains the default joint positions and velocities
- Return type
Example:
>>> state = prim.get_joints_default_state() >>> state <omni.isaac.core.utils.types.JointsState object at 0x7f04a0061240> >>> >>> state.positions [ 0.012 -0.57000005 0. -2.81 0. 3.037 0.785398 0.04 0.04 ] >>> state.velocities [0. 0. 0. 0. 0. 0. 0. 0. 0.]
- get_joints_state() omni.isaac.core.utils.types.JointsState
Get the current joint states (positions and velocities)
- Returns
an object that contains the current joint positions and velocities
- Return type
Example:
>>> state = prim.get_joints_state() >>> state <omni.isaac.core.utils.types.JointsState object at 0x7f02f6df57b0> >>> >>> state.positions [ 1.1999920e-02 -5.6962633e-01 1.3480479e-08 -2.8105433e+00 6.8284894e-06 3.0301569e+00 7.3234749e-01 3.9912373e-02 3.9999999e-02] >>> state.velocities [ 1.91603772e-06 -7.67638255e-03 -2.19138826e-07 1.10636465e-02 -4.63412944e-05 245539e-02 8.84692147e-02 5.40335372e-04 1.02849208e-05]
- get_linear_velocity() numpy.ndarray
Get the linear velocity of the root articulation prim
- Returns
3D linear velocity vector. Shape (3,)
- Return type
np.ndarray
Example:
>>> prim.get_linear_velocity() [0. 0. 0.]
- get_local_pose() Tuple[numpy.ndarray, numpy.ndarray]
Get prim’s pose with respect to the local frame (the prim’s parent frame)
- Returns
first index is the position in the local frame (with shape (3, )). Second index is quaternion orientation (with shape (4, )) in the local frame
- Return type
Tuple[np.ndarray, np.ndarray]
Example:
>>> # if the prim is in position (1.0, 0.5, 0.0) with respect to the world frame >>> position, orientation = prim.get_local_pose() >>> position [0. 0. 0.] >>> orientation [0. 0. 0.]
- get_local_scale() numpy.ndarray
Get prim’s scale with respect to the local frame (the parent’s frame)
- Returns
scale applied to the prim’s dimensions in the local frame. shape is (3, ).
- Return type
np.ndarray
Example:
>>> prim.get_local_scale() [1. 1. 1.]
- get_measured_joint_efforts(joint_indices: Optional[Union[List, numpy.ndarray]] = None) numpy.ndarray
Returns the efforts computed/measured by the physics solver of the joint forces in the DOF motion direction
- Parameters
joint_indices (Optional[Union[List, np.ndarray]], optional) – indices to specify which joints to read. Defaults to None (all joints)
- Raises
Exception – If the handlers are not initialized
- Returns
all or selected articulation joint measured efforts
- Return type
np.ndarray
Example:
>>> # get all joint efforts >>> prim.get_measured_joint_efforts() [ 2.7897308e-06 -6.9083519e+00 -3.6398471e-06 1.9158335e+01 -4.3552645e-06 1.1866090e+00 -4.7079347e-06 3.2339853e-04 -3.2044132e-04] >>> >>> # get finger efforts: panda_finger_joint1 (7) and panda_finger_joint2 (8) >>> prim.get_measured_joint_efforts(joint_indices=np.array([7, 8])) [ 0.0003234 -0.00032044]
- get_measured_joint_forces(joint_indices: Optional[Union[List, numpy.ndarray]] = None) numpy.ndarray
Get the measured joint reaction forces and torques (link incoming joint forces and torques) to external loads
Note
Since the name->index map for joints has not been exposed yet, it is possible to access the joint names and their indices through the articulation metadata.
prim._articulation_view._metadata.joint_names # list of names prim._articulation_view._metadata.joint_indices # dict of name: index
To retrieve a specific row for the link incoming joint force/torque use
joint_index + 1- Parameters
joint_indices (Optional[Union[List, np.ndarray]], optional) – indices to specify which joints to read. Defaults to None (all joints)
- Raises
Exception – If the handlers are not initialized
- Returns
measured joint forces and torques. Shape is (num_joint + 1, 6). Row index 0 is the incoming joint of the base link. For the last dimension the first 3 values are for forces and the last 3 for torques
- Return type
np.ndarray
Example:
>>> # get all measured joint forces and torques >>> prim.get_measured_joint_forces() [[ 0.0000000e+00 0.0000000e+00 0.0000000e+00 0.0000000e+00 0.0000000e+00 0.0000000e+00] [ 1.4995076e+02 4.2574748e-06 5.6364370e-04 4.8701895e-05 -6.9072924e+00 3.1881387e-05] [-2.8971717e-05 -1.0677823e+02 -6.8384506e+01 -6.9072924e+00 -5.4927128e-05 6.1222494e-07] [ 8.7120995e+01 -4.3871860e-05 -5.5795174e+01 5.3687054e-05 -2.4538563e+01 1.3333466e-05] [ 5.3519474e-05 -4.8109909e+01 6.0709282e+01 1.9157074e+01 -5.9258469e-05 8.2744418e-07] [-3.1691040e+01 2.3313689e-04 3.9990173e+01 -5.8968733e-05 -1.1863431e+00 2.2335558e-05] [-1.0809851e-04 1.5340537e+01 -1.5458489e+01 1.1863426e+00 6.1094368e-05 -1.5940281e-05] [-7.5418940e+00 -5.0814648e+00 -5.6512990e+00 -5.6385466e-05 3.8859999e-01 -3.4943256e-01] [ 4.7421460e+00 -3.1945827e+00 3.5528181e+00 5.5852943e-05 8.4794536e-03 7.6405057e-03] [ 4.0760727e+00 2.1640673e-01 -4.0513167e+00 -5.9565349e-04 1.1407082e-02 2.1432268e-06] [ 5.1680198e-03 -9.7754575e-02 -9.7093947e-02 -8.4155556e-12 -1.2910691e-12 -1.9347857e-11] [-5.1910793e-03 9.7588278e-02 -9.7106412e-02 8.4155573e-12 1.2910637e-12 -1.9347855e-11]] >>> >>> # get measured joint force and torque for the fingers >>> metadata = prim._articulation_view._metadata >>> joint_indices = 1 + np.array([ ... metadata.joint_indices["panda_finger_joint1"], ... metadata.joint_indices["panda_finger_joint2"], ... ]) >>> joint_indices [10 11] >>> prim.get_measured_joint_forces(joint_indices) [[ 5.1680198e-03 -9.7754575e-02 -9.7093947e-02 -8.4155556e-12 -1.2910691e-12 -1.9347857e-11] [-5.1910793e-03 9.7588278e-02 -9.7106412e-02 8.4155573e-12 1.2910637e-12 -1.9347855e-11]]
- get_sleep_threshold() float
Get the threshold for articulations to enter a sleep state
Search for Articulations and Sleeping in PhysX docs for more details
- Returns
sleep threshold
- Return type
float
Example:
>>> prim.get_sleep_threshold() 0.005
- get_solver_position_iteration_count() int
Get the solver (position) iteration count for the articulation
The solver iteration count determines how accurately contacts, drives, and limits are resolved. Search for Solver Iteration Count in PhysX docs for more details.
- Returns
position iteration count
- Return type
int
Example:
>>> prim.get_solver_position_iteration_count() 32
- get_solver_velocity_iteration_count() int
Get the solver (velocity) iteration count for the articulation
The solver iteration count determines how accurately contacts, drives, and limits are resolved. Search for Solver Iteration Count in PhysX docs for more details.
- Returns
velocity iteration count
- Return type
int
Example:
>>> prim.get_solver_velocity_iteration_count() 32
- get_stabilization_threshold() float
Get the mass-normalized kinetic energy below which the articulation may participate in stabilization
Search for Stabilization Threshold in PhysX docs for more details
- Returns
stabilization threshold
- Return type
float
Example:
>>> prim.get_stabilization_threshold() 0.0009999999
- get_visibility() bool
- Returns
true if the prim is visible in stage. false otherwise.
- Return type
bool
Example:
>>> # get the visible state of an visible prim on the stage >>> prim.get_visibility() True
- get_world_pose() Tuple[numpy.ndarray, numpy.ndarray]
Get prim’s pose with respect to the world’s frame
- Returns
first index is the position in the world frame (with shape (3, )). Second index is quaternion orientation (with shape (4, )) in the world frame
- Return type
Tuple[np.ndarray, np.ndarray]
Example:
>>> # if the prim is in position (1.0, 0.5, 0.0) with respect to the world frame >>> position, orientation = prim.get_world_pose() >>> position [1. 0.5 0. ] >>> orientation [1. 0. 0. 0.]
- get_world_scale() numpy.ndarray
Get prim’s scale with respect to the world’s frame
- Returns
scale applied to the prim’s dimensions in the world frame. shape is (3, ).
- Return type
np.ndarray
Example:
>>> prim.get_world_scale() [1. 1. 1.]
- get_world_velocity() numpy.ndarray
Get the articulation root velocity
- Returns
current velocity of the the root prim. Shape (3,).
- Return type
np.ndarray
- property handles_initialized: bool
Check if articulation handler is initialized
- Returns
whether the handler was initialized
- Return type
bool
Example:
>>> prim.handles_initialized True
- initialize(physics_sim_view: Optional[omni.physics.tensors.bindings._physicsTensors.SimulationView] = None) None
Create a physics simulation view if not passed and an articulation view using PhysX tensor API
Note
If the articulation has been added to the world scene (e.g.,
world.scene.add(prim)), it will be automatically initialized when the world is reset (e.g.,world.reset()).Warning
This method needs to be called after each hard reset (e.g., Stop + Play on the timeline) before interacting with any other class method.
- Parameters
physics_sim_view (omni.physics.tensors.SimulationView, optional) – current physics simulation view. Defaults to None.
Example:
>>> prim.initialize()
- is_valid() bool
Check if the prim path has a valid USD Prim at it
- Returns
True is the current prim path corresponds to a valid prim in stage. False otherwise.
- Return type
bool
Example:
>>> # given an existing and valid prim >>> prims.is_valid() True
- is_visual_material_applied() bool
Check if there is a visual material applied
- Returns
True if there is a visual material applied. False otherwise.
- Return type
bool
Example:
>>> # given a visual material applied >>> prim.is_visual_material_applied() True
- property name: Optional[str]
Returns: str: name given to the prim when instantiating it. Otherwise None.
- property non_root_articulation_link: bool
Used to query if the prim is a non root articulation link
- Returns
True if the prim itself is a non root link
- Return type
bool
Example:
>>> # for a wrapped articulation (where the root prim has the Physics Articulation Root property applied) >>> prim.non_root_articulation_link False
- property num_bodies: int
Number of articulation links
- Returns
number of links
- Return type
int
Example:
>>> prim.num_bodies 9
- property num_dof: int
Number of DOF of the articulation
- Returns
amount of DOFs
- Return type
int
Example:
>>> prim.num_dof 9
- post_reset() None
Reset the prim to its default state (position and orientation).
Note
For an articulation, in addition to configuring the root prim’s default position and spatial orientation (defined via the
set_default_statemethod), the joint’s positions, velocities, and efforts (defined via theset_joints_default_statemethod) are imposedExample:
>>> prim.post_reset()
- property prim: pxr.Usd.Prim
Returns: Usd.Prim: USD Prim object that this object holds.
- property prim_path: str
Returns: str: prim path in the stage
- set_angular_velocity(velocity: numpy.ndarray) None
Set the angular velocity of the root articulation prim
Warning
This method will immediately set the articulation state
- Parameters
velocity (np.ndarray) – 3D angular velocity vector. Shape (3,)
Hint
This method belongs to the methods used to set the articulation kinematic state:
set_linear_velocity,set_angular_velocity,set_joint_positions,set_joint_velocities,set_joint_effortsExample:
>>> prim.set_angular_velocity(np.array([0.1, 0.0, 0.0]))
- set_default_state(position: Optional[Sequence[float]] = None, orientation: Optional[Sequence[float]] = None) None
Set the default state of the prim (position and orientation), that will be used after each reset.
- Parameters
position (Optional[Sequence[float]], optional) – position in the world frame of the prim. shape is (3, ). Defaults to None, which means left unchanged.
orientation (Optional[Sequence[float]], optional) – quaternion orientation in the world frame of the prim. quaternion is scalar-first (w, x, y, z). shape is (4, ). Defaults to None, which means left unchanged.
Example:
>>> # configure default state >>> prim.set_default_state(position=np.array([1.0, 0.5, 0.0]), orientation=np.array([1, 0, 0, 0])) >>> >>> # set default states during post-reset >>> prim.post_reset()
- set_enabled_self_collisions(flag: bool) None
Set the enable self collisions flag (
physxArticulation:enabledSelfCollisions)- Parameters
flag (bool) – whether to enable self collisions
Example:
>>> prim.set_enabled_self_collisions(True)
- set_joint_efforts(efforts: numpy.ndarray, joint_indices: Optional[Union[List, numpy.ndarray]] = None) None
Set the articulation joint efforts
Note
This method can be used for effort control. For this purpose, there must be no joint drive or the stiffness and damping must be set to zero.
- Parameters
efforts (np.ndarray) – articulation joint efforts
joint_indices (Optional[Union[list, np.ndarray]], optional) – indices to specify which joints to manipulate. Defaults to None (all joints)
Hint
This method belongs to the methods used to set the articulation kinematic state:
set_linear_velocity,set_angular_velocity,set_joint_positions,set_joint_velocities,set_joint_effortsExample:
>>> # set all the robot joint efforts to 0.0 >>> prim.set_joint_efforts(np.array([0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0])) >>> >>> # set only the fingers efforts: panda_finger_joint1 (7) and panda_finger_joint2 (8) to 10 >>> prim.set_joint_efforts(np.array([10, 10]), joint_indices=np.array([7, 8]))
- set_joint_positions(positions: numpy.ndarray, joint_indices: Optional[Union[List, numpy.ndarray]] = None) None
Set the articulation joint positions
Warning
This method will immediately set (teleport) the affected joints to the indicated value. Use the
apply_actionmethod to control robot joints.- Parameters
positions (np.ndarray) – articulation joint positions
joint_indices (Optional[Union[list, np.ndarray]], optional) – indices to specify which joints to manipulate. Defaults to None (all joints)
Hint
This method belongs to the methods used to set the articulation kinematic state:
set_linear_velocity,set_angular_velocity,set_joint_positions,set_joint_velocities,set_joint_effortsExample:
>>> # set all the robot joints >>> prim.set_joint_positions(np.array([0.0, -1.0, 0.0, -2.2, 0.0, 2.4, 0.8, 0.04, 0.04])) >>> >>> # set only the fingers in closed position: panda_finger_joint1 (7) and panda_finger_joint2 (8) to 0.0 >>> prim.set_joint_positions(np.array([0.04, 0.04]), joint_indices=np.array([7, 8]))
- set_joint_velocities(velocities: numpy.ndarray, joint_indices: Optional[Union[List, numpy.ndarray]] = None) None
Set the articulation joint velocities
Warning
This method will immediately set the affected joints to the indicated value. Use the
apply_actionmethod to control robot joints.- Parameters
velocities (np.ndarray) – articulation joint velocities
joint_indices (Optional[Union[list, np.ndarray]], optional) – indices to specify which joints to manipulate. Defaults to None (all joints)
Hint
This method belongs to the methods used to set the articulation kinematic state:
set_linear_velocity,set_angular_velocity,set_joint_positions,set_joint_velocities,set_joint_effortsExample:
>>> # set all the robot joint velocities to 0.0 >>> prim.set_joint_velocities(np.array([0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0])) >>> >>> # set only the fingers velocities: panda_finger_joint1 (7) and panda_finger_joint2 (8) to -0.01 >>> prim.set_joint_velocities(np.array([-0.01, -0.01]), joint_indices=np.array([7, 8]))
- set_joints_default_state(positions: Optional[numpy.ndarray] = None, velocities: Optional[numpy.ndarray] = None, efforts: Optional[numpy.ndarray] = None) None
Set the joint default states (positions, velocities and/or efforts) to be applied after each reset.
Note
The default states will be set during post-reset (e.g., calling
.post_reset()orworld.reset()methods)- Parameters
positions (Optional[np.ndarray], optional) – joint positions. Defaults to None.
velocities (Optional[np.ndarray], optional) – joint velocities. Defaults to None.
efforts (Optional[np.ndarray], optional) – joint efforts. Defaults to None.
Example:
>>> # configure default joint states >>> prim.set_joints_default_state( ... positions=np.array([0.0, -1.0, 0.0, -2.2, 0.0, 2.4, 0.8, 0.04, 0.04]), ... velocities=np.zeros(shape=(prim.num_dof,)), ... efforts=np.zeros(shape=(prim.num_dof,)) ... ) >>> >>> # set default states during post-reset >>> prim.post_reset()
- set_linear_velocity(velocity: numpy.ndarray) None
Set the linear velocity of the root articulation prim
Warning
This method will immediately set the articulation state
- Parameters
velocity (np.ndarray) – 3D linear velocity vector. Shape (3,).
Hint
This method belongs to the methods used to set the articulation kinematic state:
set_linear_velocity,set_angular_velocity,set_joint_positions,set_joint_velocities,set_joint_effortsExample:
>>> prim.set_linear_velocity(np.array([0.1, 0.0, 0.0]))
- set_local_pose(translation: Optional[Sequence[float]] = None, orientation: Optional[Sequence[float]] = None) None
Set prim’s pose with respect to the local frame (the prim’s parent frame).
Warning
This method will change (teleport) the prim pose immediately to the indicated value
- Parameters
translation (Optional[Sequence[float]], optional) – translation in the local frame of the prim (with respect to its parent prim). shape is (3, ). Defaults to None, which means left unchanged.
orientation (Optional[Sequence[float]], optional) – quaternion orientation in the local frame of the prim. quaternion is scalar-first (w, x, y, z). shape is (4, ). Defaults to None, which means left unchanged.
Hint
This method belongs to the methods used to set the prim state
Example:
>>> prim.set_local_pose(translation=np.array([1.0, 0.5, 0.0]), orientation=np.array([1., 0., 0., 0.]))
- set_local_scale(scale: Optional[Sequence[float]]) None
Set prim’s scale with respect to the local frame (the prim’s parent frame).
- Parameters
scale (Optional[Sequence[float]]) – scale to be applied to the prim’s dimensions. shape is (3, ). Defaults to None, which means left unchanged.
Example:
>>> # scale prim 10 times smaller >>> prim.set_local_scale(np.array([0.1, 0.1, 0.1]))
- set_sleep_threshold(threshold: float) None
Set the threshold for articulations to enter a sleep state
Search for Articulations and Sleeping in PhysX docs for more details
- Parameters
threshold (float) – sleep threshold
Example:
>>> prim.set_sleep_threshold(0.01)
- set_solver_position_iteration_count(count: int) None
Set the solver (position) iteration count for the articulation
The solver iteration count determines how accurately contacts, drives, and limits are resolved. Search for Solver Iteration Count in PhysX docs for more details.
Warning
Setting a higher number of iterations may improve the fidelity of the simulation, although it may affect its performance.
- Parameters
count (int) – position iteration count
Example:
>>> prim.set_solver_position_iteration_count(64)
- set_solver_velocity_iteration_count(count: int)
Set the solver (velocity) iteration count for the articulation
The solver iteration count determines how accurately contacts, drives, and limits are resolved. Search for Solver Iteration Count in PhysX docs for more details.
Warning
Setting a higher number of iterations may improve the fidelity of the simulation, although it may affect its performance.
- Parameters
count (int) – velocity iteration count
Example:
>>> prim.set_solver_velocity_iteration_count(64)
- set_stabilization_threshold(threshold: float) None
Set the mass-normalized kinetic energy below which the articulation may participate in stabilization
Search for Stabilization Threshold in PhysX docs for more details
- Parameters
threshold (float) – stabilization threshold
Example:
>>> prim.set_stabilization_threshold(0.005)
- set_visibility(visible: bool) None
Set the visibility of the prim in stage
- Parameters
visible (bool) – flag to set the visibility of the usd prim in stage.
Example:
>>> # make prim not visible in the stage >>> prim.set_visibility(visible=False)
- set_world_pose(position: Optional[Sequence[float]] = None, orientation: Optional[Sequence[float]] = None) None
Ses prim’s pose with respect to the world’s frame
Warning
This method will change (teleport) the prim pose immediately to the indicated value
- Parameters
position (Optional[Sequence[float]], optional) – position in the world frame of the prim. shape is (3, ). Defaults to None, which means left unchanged.
orientation (Optional[Sequence[float]], optional) – quaternion orientation in the world frame of the prim. quaternion is scalar-first (w, x, y, z). shape is (4, ). Defaults to None, which means left unchanged.
Hint
This method belongs to the methods used to set the prim state
Example:
>>> prim.set_world_pose(position=np.array([1.0, 0.5, 0.0]), orientation=np.array([1., 0., 0., 0.]))
- set_world_velocity(velocity: numpy.ndarray)
Set the articulation root velocity
- Parameters
velocity (np.ndarray) – linear and angular velocity to set the root prim to. Shape (6,).
ArticulationView
- class ArticulationView(prim_paths_expr: Union[str, List[str]], name: str = 'articulation_prim_view', positions: Optional[Union[numpy.ndarray, torch.Tensor, warp.types.array]] = None, translations: Optional[Union[numpy.ndarray, torch.Tensor, warp.types.array]] = None, orientations: Optional[Union[numpy.ndarray, torch.Tensor, warp.types.array]] = None, scales: Optional[Union[numpy.ndarray, torch.Tensor, warp.types.array]] = None, visibilities: Optional[Union[numpy.ndarray, torch.Tensor, warp.types.array]] = None, reset_xform_properties: bool = True)
High level wrapper to deal with prims (one or many) that have the Root Articulation API applied and their attributes/properties
This class wraps all matching articulations found at the regex provided at the
prim_paths_exprargumentNote
Each prim will have
xformOp:orient,xformOp:translateandxformOp:scaleonly post-init, unless it is a non-root articulation link.Warning
The articulation view object must be initialized in order to be able to operate on it. See the
initializemethod for more details.- Parameters
prim_paths_expr (Union[str, List[str]]) – prim paths regex to encapsulate all prims that match it. example: “/World/Env[1-5]/Franka” will match /World/Env1/Franka, /World/Env2/Franka..etc. (a non regex prim path can also be used to encapsulate one rigid prim).
name (str, optional) – shortname to be used as a key by Scene class. Note: needs to be unique if the object is added to the Scene. Defaults to “articulation_prim_view”.
positions (Optional[Union[np.ndarray, torch.Tensor, wp.array]], optional) – default positions in the world frame of the prims. shape is (N, 3). Defaults to None, which means left unchanged.
translations (Optional[Union[np.ndarray, torch.Tensor, wp.array]], optional) – default translations in the local frame of the prims (with respect to its parent prims). shape is (N, 3). Defaults to None, which means left unchanged.
orientations (Optional[Union[np.ndarray, torch.Tensor, wp.array]], optional) – default quaternion orientations in the world/ local frame of the prims (depends if translation or position is specified). quaternion is scalar-first (w, x, y, z). shape is (N, 4).
scales (Optional[Union[np.ndarray, torch.Tensor, wp.array]], optional) – local scales to be applied to the prim’s dimensions in the view. shape is (N, 3). Defaults to None, which means left unchanged.
visibilities (Optional[Union[np.ndarray, torch.Tensor, wp.array]], optional) – set to false for an invisible prim in the stage while rendering. shape is (N,). Defaults to None.
reset_xform_properties (bool, optional) – True if the prims don’t have the right set of xform properties (i.e: translate, orient and scale) ONLY and in that order. Set this parameter to False if the object were cloned using using the cloner api in omni.isaac.cloner. Defaults to True.
Example:
>>> import omni.isaac.core.utils.stage as stage_utils >>> from omni.isaac.cloner import GridCloner >>> from omni.isaac.core.articulations import ArticulationView >>> from pxr import UsdGeom >>> >>> usd_path = "/home/<user>/Documents/Assets/Robots/Franka/franka_alt_fingers.usd" >>> env_zero_path = "/World/envs/env_0" >>> num_envs = 5 >>> >>> # load the Franka Panda robot USD file >>> stage_utils.add_reference_to_stage(usd_path, prim_path=f"{env_zero_path}/panda") # /World/envs/env_0/panda >>> >>> # clone the environment (num_envs) >>> cloner = GridCloner(spacing=1.5) >>> cloner.define_base_env(env_zero_path) >>> UsdGeom.Xform.Define(stage_utils.get_current_stage(), env_zero_path) >>> cloner.clone(source_prim_path=env_zero_path, prim_paths=cloner.generate_paths("/World/envs/env", num_envs)) >>> >>> # wrap all articulations >>> prims = ArticulationView(prim_paths_expr="/World/envs/env.*/panda", name="franka_panda_view") >>> prims <omni.isaac.core.articulations.articulation_view.ArticulationView object at 0x7ff174054b20>
- apply_action(control_actions: omni.isaac.core.utils.types.ArticulationActions, indices: Optional[Union[numpy.ndarray, List, torch.Tensor, warp.types.array]] = None) None
Apply joint positions (targets), velocities (targets) and/or efforts to control an articulation
Note
This method can be used instead of the separate
set_joint_position_targets,set_joint_velocity_targetsandset_joint_efforts- Parameters
control_actions (ArticulationActions) – actions to be applied for next physics step.
indices (Optional[Union[np.ndarray, List, torch.Tensor, wp.array]], optional) – indices to specify which prims to manipulate. Shape (M,). Where M <= size of the encapsulated prims in the view. Defaults to None (i.e: all prims in the view).
Hint
High stiffness makes the joints snap faster and harder to the desired target, and higher damping smoothes but also slows down the joint’s movement to target
For position control, set relatively high stiffness and low damping (to reduce vibrations)
For velocity control, stiffness must be set to zero with a non-zero damping
For effort control, stiffness and damping must be set to zero
Example:
>>> from omni.isaac.core.utils.types import ArticulationActions >>> >>> # move all the articulation joints to the indicated position. >>> # Since there are 5 envs, the joint positions are repeated 5 times >>> positions = np.tile(np.array([0.0, -1.0, 0.0, -2.2, 0.0, 2.4, 0.8, 0.04, 0.04]), (num_envs, 1)) >>> action = ArticulationActions(joint_positions=positions) >>> prims.apply_action(action) >>> >>> # close the robot fingers: panda_finger_joint1 (7) and panda_finger_joint2 (8) to 0.0 >>> # for the first, middle and last of the 5 envs >>> positions = np.tile(np.array([0.0, 0.0]), (3, 1)) >>> action = ArticulationActions(joint_positions=positions, joint_indices=np.array([7, 8])) >>> prims.apply_action(action, indices=np.array([0, 2, 4]))
- apply_visual_materials(visual_materials: Union[omni.isaac.core.materials.visual_material.VisualMaterial, List[omni.isaac.core.materials.visual_material.VisualMaterial]], weaker_than_descendants: Optional[Union[bool, List[bool]]] = None, indices: Optional[Union[numpy.ndarray, list, torch.Tensor, warp.types.array]] = None) None
Apply visual material to the prims and optionally their prim descendants.
- Parameters
visual_materials (Union[VisualMaterial, List[VisualMaterial]]) – visual materials to be applied to the prims. Currently supports PreviewSurface, OmniPBR and OmniGlass. If a list is provided then its size has to be equal the view’s size or indices size. If one material is provided it will be applied to all prims in the view.
weaker_than_descendants (Optional[Union[bool, List[bool]]], optional) – True if the material shouldn’t override the descendants materials, otherwise False. Defaults to False. If a list of visual materials is provided then a list has to be provided with the same size for this arg as well.
indices (Optional[Union[np.ndarray, list, torch.Tensor, wp.array]], optional) – indices to specify which prims to manipulate. Shape (M,). Where M <= size of the encapsulated prims in the view. Defaults to None (i.e: all prims in the view).
- Raises
Exception – length of visual materials != length of prims indexed
Exception – length of visual materials != length of weaker descendants bools arg
Example:
>>> from omni.isaac.core.materials import OmniGlass >>> >>> # create a dark-red glass visual material >>> material = OmniGlass( ... prim_path="/World/material/glass", # path to the material prim to create ... ior=1.25, ... depth=0.001, ... thin_walled=False, ... color=np.array([0.5, 0.0, 0.0]) ... ) >>> prims.apply_visual_materials(material)
- property body_names: List[str]
List of prim names for each rigid body (link) of the articulations
- Returns
ordered names of bodies that corresponds to links for the articulations in the view
- Return type
List[str]
Example:
>>> prims.body_names ['panda_link0', 'panda_link1', 'panda_link2', 'panda_link3', 'panda_link4', 'panda_link5', 'panda_link6', 'panda_link7', 'panda_link8', 'panda_hand', 'panda_leftfinger', 'panda_rightfinger']
- property count: int
- Returns
Number of prims encapsulated in this view.
- Return type
int
Example:
>>> prims.count 5
- property dof_names: List[str]
List of prim names for each DOF of the articulations
- Returns
ordered names of joints that corresponds to degrees of freedom for the articulations in the view
- Return type
List[str]
Example:
>>> prims.dof_names ['panda_joint1', 'panda_joint2', 'panda_joint3', 'panda_joint4', 'panda_joint5', 'panda_joint6', 'panda_joint7', 'panda_finger_joint1', 'panda_finger_joint2']
- get_angular_velocities(indices: Optional[Union[numpy.ndarray, list, torch.Tensor, warp.types.array]] = None, clone: bool = True) Union[numpy.ndarray, torch.Tensor, warp.types.indexedarray]
Get the angular velocities of prims in the view.
- Parameters
indices (Optional[Union[np.ndarray, list, torch.Tensor, wp.array]], optional) – indices to specify which prims to query. Shape (M,). Where M <= size of the encapsulated prims in the view. Defaults to None (i.e: all prims in the view)
clone (bool, optional) – True to return a clone of the internal buffer. Otherwise False. Defaults to True.
- Returns
angular velocities of the prims in the view. shape is (M, 3).
- Return type
Union[np.ndarray, torch.Tensor, wp.indexedarray]
Example:
>>> # get all articulation angular velocities. Returned shape is (5, 3) for the example: 5 envs, angular (3) >>> prims.get_angular_velocities() [[0. 0. 0.] [0. 0. 0.] [0. 0. 0.] [0. 0. 0.] [0. 0. 0.]] >>> >>> # get only the articulation angular velocities for the first, middle and last of the 5 envs >>> # Returned shape is (5, 3) for the example: 3 envs selected, angular (3) >>> prims.get_angular_velocities(indices=np.array([0, 2, 4])) [[0. 0. 0.] [0. 0. 0.] [0. 0. 0.]]
- get_applied_actions(clone: bool = True) omni.isaac.core.utils.types.ArticulationActions
Get the last applied actions
- Parameters
clone (bool, optional) – True to return clones of the internal buffers. Otherwise False. Defaults to True.
- Returns
current applied actions (i.e: current position targets and velocity targets)
- Return type
Example:
>>> # last applied action: joint_positions -> [0.0, -1.0, 0.0, -2.2, 0.0, 2.4, 0.8, 0.04, 0.04]. >>> # Returned shape is (5, 9) for the example: 5 envs, 9 DOFs >>> actions = prims.get_applied_actions() >>> actions <omni.isaac.core.utils.types.ArticulationActions object at 0x7f28af31d870> >>> actions.joint_positions [[ 0. -1. 0. -2.2 0. 2.4 0.8 0.04 0.04] [ 0. -1. 0. -2.2 0. 2.4 0.8 0.04 0.04] [ 0. -1. 0. -2.2 0. 2.4 0.8 0.04 0.04] [ 0. -1. 0. -2.2 0. 2.4 0.8 0.04 0.04] [ 0. -1. 0. -2.2 0. 2.4 0.8 0.04 0.04]] >>> actions.joint_velocities [[0. 0. 0. 0. 0. 0. 0. 0. 0.] [0. 0. 0. 0. 0. 0. 0. 0. 0.] [0. 0. 0. 0. 0. 0. 0. 0. 0.] [0. 0. 0. 0. 0. 0. 0. 0. 0.] [0. 0. 0. 0. 0. 0. 0. 0. 0.]] >>> actions.joint_efforts [[0. 0. 0. 0. 0. 0. 0. 0. 0.] [0. 0. 0. 0. 0. 0. 0. 0. 0.] [0. 0. 0. 0. 0. 0. 0. 0. 0.] [0. 0. 0. 0. 0. 0. 0. 0. 0.] [0. 0. 0. 0. 0. 0. 0. 0. 0.]]
- get_applied_joint_efforts(indices: Optional[Union[numpy.ndarray, List, torch.Tensor, warp.types.array]] = None, joint_indices: Optional[Union[numpy.ndarray, List, torch.Tensor, warp.types.array]] = None, clone: bool = True) Union[numpy.ndarray, torch.Tensor, warp.types.indexedarray]
Get the joint efforts of articulations in the view
This method will return the efforts set by the
set_joint_effortsmethod- Parameters
indices (Optional[Union[np.ndarray, List, torch.Tensor, wp.array]], optional) – indices to specify which prims to query. Shape (M,). Where M <= size of the encapsulated prims in the view. Defaults to None (i.e: all prims in the view).
joint_indices (Optional[Union[np.ndarray, List, torch.Tensor, wp.array]], optional) – joint indices to specify which joints to query. Shape (K,). Where K <= num of dofs. Defaults to None (i.e: all dofs).
clone (bool, optional) – True to return a clone of the internal buffer. Otherwise False. Defaults to True.
- Returns
joint efforts of articulations in the view. Shape is (M, K).
- Return type
Union[np.ndarray, torch.Tensor, wp.indexedarray]
Example:
>>> # get all applied joint efforts. Returned shape is (5, 9) for the example: 5 envs, 9 DOFs >>> prims.get_applied_joint_efforts() [[0. 0. 0. 0. 0. 0. 0. 0. 0.] [0. 0. 0. 0. 0. 0. 0. 0. 0.] [0. 0. 0. 0. 0. 0. 0. 0. 0.] [0. 0. 0. 0. 0. 0. 0. 0. 0.] [0. 0. 0. 0. 0. 0. 0. 0. 0.]] >>> >>> # get finger applied efforts: panda_finger_joint1 (7) and panda_finger_joint2 (8) >>> # for the first, middle and last of the 5 envs. Returned shape is (3, 2) >>> prims.get_applied_joint_efforts(indices=np.array([0, 2, 4]), joint_indices=np.array([7, 8])) [[0. 0.] [0. 0.] [0. 0.]]
- get_applied_visual_materials(indices: Optional[Union[numpy.ndarray, list, torch.Tensor, warp.types.array]] = None) List[omni.isaac.core.materials.visual_material.VisualMaterial]
Get the current applied visual materials
- Parameters
indices (Optional[Union[np.ndarray, list, torch.Tensor, wp.array]], optional) – indices to specify which prims to query. Shape (M,). Where M <= size of the encapsulated prims in the view. Defaults to None (i.e: all prims in the view).
- Returns
a list of the current applied visual materials to the prims if its type is currently supported.
- Return type
List[VisualMaterial]
Example:
>>> # get all applied visual materials. Returned size is 5 for the example: 5 envs >>> prims.get_applied_visual_materials() [<omni.isaac.core.materials.omni_glass.OmniGlass object at 0x7f829c165de0>, <omni.isaac.core.materials.omni_glass.OmniGlass object at 0x7f829c165de0>, <omni.isaac.core.materials.omni_glass.OmniGlass object at 0x7f829c165de0>, <omni.isaac.core.materials.omni_glass.OmniGlass object at 0x7f829c165de0>, <omni.isaac.core.materials.omni_glass.OmniGlass object at 0x7f829c165de0>] >>> >>> # get the applied visual materials for the first, middle and last of the 5 envs. Returned size is 3 >>> prims.get_applied_visual_materials(indices=np.array([0, 2, 4])) [<omni.isaac.core.materials.omni_glass.OmniGlass object at 0x7f829c165de0>, <omni.isaac.core.materials.omni_glass.OmniGlass object at 0x7f829c165de0>, <omni.isaac.core.materials.omni_glass.OmniGlass object at 0x7f829c165de0>]
- get_armatures(indices: Optional[Union[numpy.ndarray, List, torch.Tensor, warp.types.array]] = None, joint_indices: Optional[Union[numpy.ndarray, List, torch.Tensor, warp.types.array]] = None, clone: bool = True) Union[numpy.ndarray, torch.Tensor, warp.types.indexedarray]
Get armatures for articulation joints in the view
Search for “Joint Armature” in PhysX docs for more details.
- Parameters
indices (Optional[Union[np.ndarray, List, torch.Tensor, wp.array]], optional) – indices to specify which prims to query. Shape (M,). Where M <= size of the encapsulated prims in the view. Defaults to None (i.e: all prims in the view).
joint_indices (Optional[Union[np.ndarray, List, torch.Tensor, wp.array]], optional) – joint indices to specify which joints to query. Shape (K,). Where K <= num of dofs. Defaults to None (i.e: all dofs).
clone (Optional[bool]) – True to return a clone of the internal buffer. Otherwise False. Defaults to True.
- Returns
joint armatures for articulations in the view. shape (M, K).
- Return type
Union[np.ndarray, torch.Tensor, wp.indexedarray]
Example:
>>> # get joint armatures. Returned shape is (5, 9) for the example: 5 envs, 9 DOFs >>> prims.get_armatures() [[0. 0. 0. 0. 0. 0. 0. 0. 0.] [0. 0. 0. 0. 0. 0. 0. 0. 0.] [0. 0. 0. 0. 0. 0. 0. 0. 0.] [0. 0. 0. 0. 0. 0. 0. 0. 0.] [0. 0. 0. 0. 0. 0. 0. 0. 0.]] >>> >>> # get only the finger joint (panda_finger_joint1 (7) and panda_finger_joint2 (8)) armatures >>> # for the first, middle and last of the 5 envs. Returned shape is (3, 2) >>> prims.get_armatures(indices=np.array([0,2,4]), joint_indices=np.array([7,8])) [[0. 0.] [0. 0.] [0. 0.]]
- get_articulation_body_count() int
Get the number of rigid bodies (links) of the articulations
- Returns
maximum number of rigid bodies (links) in the articulation
- Return type
int
Example:
>>> prims.get_articulation_body_count() 12
- get_body_coms(indices: Optional[Union[numpy.ndarray, List, torch.Tensor, warp.types.array]] = None, body_indices: Optional[Union[numpy.ndarray, List, torch.Tensor, warp.types.array]] = None, clone: bool = True) Union[numpy.ndarray, torch.Tensor, warp.types.indexedarray]
Get rigid body center of mass (COM) of articulations in the view.
- Parameters
indices (Optional[Union[np.ndarray, List, torch.Tensor, wp.array]], optional) – indices to specify which prims to query. Shape (M,). Where M <= size of the encapsulated prims in the view. Defaults to None (i.e: all prims in the view).
body_indices (Optional[Union[np.ndarray, List, torch.Tensor, wp.array]], optional) – body indices to specify which bodies to query. Shape (K,). Where K <= num of bodies. Defaults to None (i.e: all bodies).
clone (bool, optional) – True to return a clone of the internal buffer. Otherwise False. Defaults to True.
- Returns
rigid body center of mass positions and orientations of articulations in the view. Position shape is (M, K, 3), orientation shape is (M, k, 4).
- Return type
Union[np.ndarray, torch.Tensor, wp.indexedarray]
Example:
>>> # get all body center of mass. Returned shape is (5, 12, 3) for positions and (5, 12, 4) for orientations >>> # for the example: 5 envs, 12 rigid bodies >>> positions, orientations = prims.get_body_coms() >>> positions [[[0. 0. 0.] [0. 0. 0.] ... [0. 0. 0.] [0. 0. 0.]]] >>> orientations [[[1. 0. 0. 0.] [1. 0. 0. 0.] ... [1. 0. 0. 0.] [1. 0. 0. 0.]]] >>> >>> # get finger body center of mass: panda_leftfinger (10) and panda_rightfinger (11) for the first, >>> # middle and last of the 5 envs. Returned shape is (3, 2, 3) for positions and (3, 2, 4) for orientations >>> positions, orientations = prims.get_body_coms(indices=np.array([0, 2, 4]), body_indices=np.array([10, 11])) >>> positions [[[0. 0. 0.] [0. 0. 0.]] [[0. 0. 0.] [0. 0. 0.]] [[0. 0. 0.] [0. 0. 0.]]] >>> orientations [[[1. 0. 0. 0.] [1. 0. 0. 0.]] [[1. 0. 0. 0.] [1. 0. 0. 0.]] [[1. 0. 0. 0.] [1. 0. 0. 0.]]]
- get_body_disable_gravity(indices: Optional[Union[numpy.ndarray, List, torch.Tensor, warp.types.array]] = None, body_indices: Optional[Union[numpy.ndarray, List, torch.Tensor, warp.types.array]] = None, clone: bool = True) Union[numpy.ndarray, torch.Tensor, warp.types.indexedarray]
Get whether the rigid bodies of articulations in the view have gravity disabled or not
- Parameters
indices (Optional[Union[np.ndarray, List, torch.Tensor, wp.array]], optional) – indices to specify which prims to query. Shape (M,). Where M <= size of the encapsulated prims in the view. Defaults to None (i.e: all prims in the view).
body_indices (Optional[Union[np.ndarray, List, torch.Tensor, wp.array]], optional) – body indices to specify which bodies to query. Shape (K,). Where K <= num of bodies. Defaults to None (i.e: all bodies).
clone (bool, optional) – True to return a clone of the internal buffer. Otherwise False. Defaults to True.
- Returns
rigid body gravity activation of articulations in the view. Shape is (M, K).
- Return type
Union[np.ndarray, torch.Tensor, wp.indexedarray]
- get_body_index(body_name: str) int
Get a ridig body (link) index in the articulation view given its name
- Parameters
body_name (str) – name of the ridig body to query
- Returns
index of the rigid body in the articulation buffers
- Return type
int
Example:
>>> # get the index of the left finger: panda_leftfinger >>> prims.get_body_index("panda_leftfinger") 10
- get_body_inertias(indices: Optional[Union[numpy.ndarray, List, torch.Tensor, warp.types.array]] = None, body_indices: Optional[Union[numpy.ndarray, List, torch.Tensor, warp.types.array]] = None, clone: bool = True) Union[numpy.ndarray, torch.Tensor, warp.types.indexedarray]
Get rigid body inertias of articulations in the view
- Parameters
indices (Optional[Union[np.ndarray, List, torch.Tensor, wp.array]], optional) – indices to specify which prims to query. Shape (M,). Where M <= size of the encapsulated prims in the view. Defaults to None (i.e: all prims in the view).
body_indices (Optional[Union[np.ndarray, List, torch.Tensor, wp.array]], optional) – body indices to specify which bodies to query. Shape (K,). Where K <= num of bodies. Defaults to None (i.e: all bodies).
clone (bool, optional) – True to return a clone of the internal buffer. Otherwise False. Defaults to True.
- Returns
rigid body inertias of articulations in the view. Shape is (M, K, 9).
- Return type
Union[np.ndarray, torch.Tensor, wp.indexedarray]
Example:
>>> # get all body inertias. Returned shape is (5, 12, 9) for the example: 5 envs, 12 rigid bodies >>> prims.get_body_inertias() [[[1.2988697e-06 0.0 0.0 0.0 1.6535528e-06 0.0 0.0 0.0 2.0331163e-06] [1.8686389e-06 0.0 0.0 0.0 1.4378986e-06 0.0 0.0 0.0 9.0681192e-07] ... [4.2041304e-10 0.0 0.0 0.0 3.9026365e-10 0.0 0.0 0.0 1.3347495e-10] [4.2041304e-10 0.0 0.0 0.0 3.9026365e-10 0.0 0.0 0.0 1.3347495e-10]]] >>> >>> # get finger body inertias: panda_leftfinger (10) and panda_rightfinger (11) >>> # for the first, middle and last of the 5 envs. Returned shape is (3, 2, 9) >>> prims.get_body_inertias(indices=np.array([0, 2, 4]), body_indices=np.array([10, 11])) [[[4.2041304e-10 0.0 0.0 0.0 3.9026365e-10 0.0 0.0 0.0 1.3347495e-10] [4.2041304e-10 0.0 0.0 0.0 3.9026365e-10 0.0 0.0 0.0 1.3347495e-10]] ... [[4.2041304e-10 0.0 0.0 0.0 3.9026365e-10 0.0 0.0 0.0 1.3347495e-10] [4.2041304e-10 0.0 0.0 0.0 3.9026365e-10 0.0 0.0 0.0 1.3347495e-10]]]
- get_body_inv_inertias(indices: Optional[Union[numpy.ndarray, List, torch.Tensor, warp.types.array]] = None, body_indices: Optional[Union[numpy.ndarray, List, torch.Tensor, warp.types.array]] = None, clone: bool = True) Union[numpy.ndarray, torch.Tensor, warp.types.indexedarray]
Get rigid body inverse inertias of articulations in the view
- Parameters
indices (Optional[Union[np.ndarray, List, torch.Tensor, wp.array]], optional) – indices to specify which prims to query. Shape (M,). Where M <= size of the encapsulated prims in the view. Defaults to None (i.e: all prims in the view).
body_indices (Optional[Union[np.ndarray, List, torch.Tensor, wp.array]], optional) – body indices to specify which bodies to query. Shape (K,). Where K <= num of bodies. Defaults to None (i.e: all bodies).
clone (bool, optional) – True to return a clone of the internal buffer. Otherwise False. Defaults to True.
- Returns
rigid body inverse inertias of articulations in the view. Shape is (M, K, 9).
- Return type
Union[np.ndarray, torch.Tensor, wp.indexedarray]
Example:
>>> # get all body inverse inertias. Returned shape is (5, 12, 9) for the example: 5 envs, 12 rigid bodies >>> prims.get_body_inv_inertias() [[[7.6990012e+05 0.0 0.0 0.0 6.0475844e+05 0.0 0.0 0.0 4.9185578e+05] [5.3514888e+05 0.0 0.0 0.0 6.9545931e+05 0.0 0.0 0.0 1.1027645e+06] ... [2.3786132e+09 0.0 0.0 0.0 2.5623703e+09 0.0 0.0 0.0 7.4920422e+09] [2.3786132e+09 0.0 0.0 0.0 2.5623703e+09 0.0 0.0 0.0 7.4920422e+09]]] >>> >>> # get finger body inverse inertias: panda_leftfinger (10) and panda_rightfinger (11) >>> # for the first, middle and last of the 5 envs. Returned shape is (3, 2, 9) >>> prims.get_body_inv_inertias(indices=np.array([0, 2, 4]), body_indices=np.array([10, 11])) [[[2.3786132e+09 0.0 0.0 0.0 2.5623703e+09 0.0 0.0 0.0 7.4920422e+09] [2.3786132e+09 0.0 0.0 0.0 2.5623703e+09 0.0 0.0 0.0 7.4920422e+09]] ... [[2.3786132e+09 0.0 0.0 0.0 2.5623703e+09 0.0 0.0 0.0 7.4920422e+09] [2.3786132e+09 0.0 0.0 0.0 2.5623703e+09 0.0 0.0 0.0 7.4920422e+09]]]
- get_body_inv_masses(indices: Optional[Union[numpy.ndarray, List, torch.Tensor, warp.types.array]] = None, body_indices: Optional[Union[numpy.ndarray, List, torch.Tensor, warp.types.array]] = None, clone: bool = True) Union[numpy.ndarray, torch.Tensor, warp.types.indexedarray]
Get rigid body inverse masses of articulations in the view
- Parameters
indices (Optional[Union[np.ndarray, List, torch.Tensor, wp.array]], optional) – indices to specify which prims to query. Shape (M,). Where M <= size of the encapsulated prims in the view. Defaults to None (i.e: all prims in the view).
body_indices (Optional[Union[np.ndarray, List, torch.Tensor, wp.array]], optional) – body indices to specify which bodies to query. Shape (K,). Where K <= num of bodies. Defaults to None (i.e: all bodies).
clone (bool, optional) – True to return a clone of the internal buffer. Otherwise False. Defaults to True.
- Returns
rigid body inverse masses of articulations in the view. Shape is (M, K).
- Return type
Union[np.ndarray, torch.Tensor, wp.indexedarray]
Example:
>>> # get all body inverse masses. Returned shape is (5, 12) for the example: 5 envs, 12 rigid bodies >>> prims.get_body_inv_masses() [[ 0.35534042 0.42372888 0.42025304 0.37737525 0.3710848 0.33542618 0.8860687 2.4673615 10. 1.7910539 71.14793 71.14793] [ 0.35534042 0.42372888 0.42025304 0.37737525 0.3710848 0.33542618 0.8860687 2.4673615 10. 1.7910539 71.14793 71.14793] [ 0.35534042 0.42372888 0.42025304 0.37737525 0.3710848 0.33542618 0.8860687 2.4673615 10. 1.7910539 71.14793 71.14793] [ 0.35534042 0.42372888 0.42025304 0.37737525 0.3710848 0.33542618 0.8860687 2.4673615 10. 1.7910539 71.14793 71.14793] [ 0.35534042 0.42372888 0.42025304 0.37737525 0.3710848 0.33542618 0.8860687 2.4673615 10. 1.7910539 71.14793 71.14793]] >>> >>> # get finger body inverse masses: panda_leftfinger (10) and panda_rightfinger (11) >>> # for the first, middle and last of the 5 envs. Returned shape is (3, 2) >>> prims.get_body_inv_masses(indices=np.array([0, 2, 4]), body_indices=np.array([10, 11])) [[71.14793 71.14793] [71.14793 71.14793] [71.14793 71.14793]]
- get_body_masses(indices: Optional[Union[numpy.ndarray, List, torch.Tensor, warp.types.array]] = None, body_indices: Optional[Union[numpy.ndarray, List, torch.Tensor, warp.types.array]] = None, clone: bool = True) Union[numpy.ndarray, torch.Tensor, warp.types.indexedarray]
Get rigid body masses of articulations in the view
- Parameters
indices (Optional[Union[np.ndarray, List, torch.Tensor, wp.array]], optional) – indices to specify which prims to query. Shape (M,). Where M <= size of the encapsulated prims in the view. Defaults to None (i.e: all prims in the view).
body_indices (Optional[Union[np.ndarray, List, torch.Tensor, wp.array]], optional) – body indices to specify which bodies to query. Shape (K,). Where K <= num of bodies. Defaults to None (i.e: all bodies).
clone (bool, optional) – True to return a clone of the internal buffer. Otherwise False. Defaults to True.
- Returns
rigid body masses of articulations in the view. Shape is (M, K).
- Return type
Union[np.ndarray, torch.Tensor, wp.indexedarray]
Example:
>>> # get all body masses. Returned shape is (5, 12) for the example: 5 envs, 12 rigid bodies >>> prims.get_body_masses() [[2.8142028 2.3599997 2.3795187 2.6498823 2.6948018 2.981282 1.1285807 0.40529126 0.1 0.5583305 0.01405522 0.01405522] [2.8142028 2.3599997 2.3795187 2.6498823 2.6948018 2.981282 1.1285807 0.40529126 0.1 0.5583305 0.01405522 0.01405522] [2.8142028 2.3599997 2.3795187 2.6498823 2.6948018 2.981282 1.1285807 0.40529126 0.1 0.5583305 0.01405522 0.01405522] [2.8142028 2.3599997 2.3795187 2.6498823 2.6948018 2.981282 1.1285807 0.40529126 0.1 0.5583305 0.01405522 0.01405522] [2.8142028 2.3599997 2.3795187 2.6498823 2.6948018 2.981282 1.1285807 0.40529126 0.1 0.5583305 0.01405522 0.01405522]] >>> >>> # get finger body masses: panda_leftfinger (10) and panda_rightfinger (11) >>> # for the first, middle and last of the 5 envs. Returned shape is (3, 2) >>> prims.get_body_masses(indices=np.array([0, 2, 4]), body_indices=np.array([10, 11])) [[0.01405522 0.01405522] [0.01405522 0.01405522] [0.01405522 0.01405522]]
- get_coriolis_and_centrifugal_forces(indices: Optional[Union[numpy.ndarray, List, torch.Tensor, warp.types.array]] = None, joint_indices: Optional[Union[numpy.ndarray, List, torch.Tensor, warp.types.array]] = None, clone: bool = True) Union[numpy.ndarray, torch.Tensor, warp.types.indexedarray]
Get the Coriolis and centrifugal forces (joint DOF forces required to counteract Coriolis and centrifugal forces for the given articulation state) of articulations in the view
Search for Coriolis and Centrifugal Forces in PhysX docs for more details
- Parameters
indices (Optional[Union[np.ndarray, List, torch.Tensor, wp.array]], optional) – indices to specify which prims to query. Shape (M,). Where M <= size of the encapsulated prims in the view. Defaults to None (i.e: all prims in the view).
joint_indices (Optional[Union[np.ndarray, List, torch.Tensor, wp.array]], optional) – joint indices to specify which joints to query. Shape (K,). Where K <= num of dofs. Defaults to None (i.e: all dofs).
clone (bool, optional) – True to return a clone of the internal buffer. Otherwise False. Defaults to True.
- Returns
Coriolis and centrifugal forces of articulations in the view. Shape is (M, K).
- Return type
Union[np.ndarray, torch.Tensor, wp.indexedarray]
Example:
>>> # get all coriolis and centrifugal forces. Returned shape is (5, 9) for the example: 5 envs, 9 DOFs >>> prims.get_coriolis_and_centrifugal_forces() [[ 1.6842524e-06 -1.8269569e-04 5.2162073e-07 -9.7677548e-05 3.0365106e-07 6.7375149e-06 6.1105780e-08 -4.6237556e-06 -4.1627968e-06] [ 1.6842524e-06 -1.8269569e-04 5.2162073e-07 -9.7677548e-05 3.0365106e-07 6.7375149e-06 6.1105780e-08 -4.6237556e-06 -4.1627968e-06] [ 1.6842561e-06 -1.8269687e-04 5.2162375e-07 -9.7677454e-05 3.0365084e-07 6.7375931e-06 6.1106007e-08 -4.6237533e-06 -4.1627954e-06] [ 1.6842561e-06 -1.8269687e-04 5.2162375e-07 -9.7677454e-05 3.0365084e-07 6.7375931e-06 6.1106007e-08 -4.6237533e-06 -4.1627954e-06] [ 1.6842524e-06 -1.8269569e-04 5.2162073e-07 -9.7677548e-05 3.0365106e-07 6.7375149e-06 6.1105780e-08 -4.6237556e-06 -4.1627968e-06]] >>> >>> # get finger joint coriolis and centrifugal forces: panda_finger_joint1 (7) and panda_finger_joint2 (8) >>> # for the first, middle and last of the 5 envs. Returned shape is (3, 2) >>> prims.get_coriolis_and_centrifugal_forces(indices=np.array([0, 2, 4]), joint_indices=np.array([7, 8])) [[-4.6237556e-06 -4.1627968e-06] [-4.6237533e-06 -4.1627954e-06] [-4.6237556e-06 -4.1627968e-06]]
- get_default_state() omni.isaac.core.utils.types.XFormPrimViewState
Get the default states (positions and orientations) defined with the
set_default_statemethod- Returns
returns the default state of the prims that is used after each reset.
- Return type
Example:
>>> state = prims.get_default_state() >>> state <omni.isaac.core.utils.types.XFormPrimViewState object at 0x7f82f73e3070> >>> state.positions [[ 1.5 -0.75 0. ] [ 1.5 0.75 0. ] [ 0. -0.75 0. ] [ 0. 0.75 0. ] [-1.5 -0.75 0. ]] >>> state.orientations [[1. 0. 0. 0.] [1. 0. 0. 0.] [1. 0. 0. 0.] [1. 0. 0. 0.] [1. 0. 0. 0.]]
- get_dof_index(dof_name: str) int
Get a DOF index in the joint buffers given its name
- Parameters
dof_name (str) – name of the joint that corresponds to the degree of freedom to query
- Returns
index of the degree of freedom in the joint buffers
- Return type
int
Example:
>>> # get the index of the left finger joint: panda_finger_joint1 >>> prims.get_dof_index("panda_finger_joint1") 7
- get_dof_limits() Union[numpy.ndarray, torch.Tensor]
Get the articulations DOFs limits (lower and upper)
- Returns
degrees of freedom position limits. Shape is (N, num_dof, 2). For the last dimension, index 0 corresponds to lower limits and index 1 corresponds to upper limits
- Return type
Union[np.ndarray, torch.Tensor, wp.array]
Example:
>>> # get DOF limits. Returned shape is (5, 9, 2) for the example: 5 envs, 9 DOFs >>> prims.get_dof_limits() [[[-2.8973 2.8973] [-1.7628 1.7628] [-2.8973 2.8973] [-3.0718 -0.0698] [-2.8973 2.8973] [-0.0175 3.7525] [-2.8973 2.8973] [ 0. 0.04 ] [ 0. 0.04 ]] ... [[-2.8973 2.8973] [-1.7628 1.7628] [-2.8973 2.8973] [-3.0718 -0.0698] [-2.8973 2.8973] [-0.0175 3.7525] [-2.8973 2.8973] [ 0. 0.04 ] [ 0. 0.04 ]]]
- get_dof_types(dof_names: Optional[List[str]] = None) List[str]
Get the DOF types given the DOF names
- Parameters
dof_names (List[str], optional) – names of the joints that corresponds to the degrees of freedom to query. Defaults to None.
- Returns
types of the joints that corresponds to the degrees of freedom. Types can be invalid, translation or rotation.
- Return type
List[str]
Example:
>>> # get all DOF types >>> prims.get_dof_types() [<DofType.Rotation: 0>, <DofType.Rotation: 0>, <DofType.Rotation: 0>, <DofType.Rotation: 0>, <DofType.Rotation: 0>, <DofType.Rotation: 0>, <DofType.Rotation: 0>, <DofType.Translation: 1>, <DofType.Translation: 1>] >>> >>> # get only the finger DOF types: panda_finger_joint1 and panda_finger_joint2 >>> prims.get_dof_types(dof_names=["panda_finger_joint1", "panda_finger_joint2"]) [<DofType.Translation: 1>, <DofType.Translation: 1>]
- get_drive_types() Union[numpy.ndarray, torch.Tensor]
Get the articulations DOFs limits (lower and upper)
- Returns
degrees of freedom position limits. Shape is (N, num_dof). For the last dimension, index 0 corresponds to lower limits and index 1 corresponds to upper limits
- Return type
Union[np.ndarray, torch.Tensor, wp.array]
- get_effort_modes(indices: Optional[Union[numpy.ndarray, List, torch.Tensor, warp.types.array]] = None, joint_indices: Optional[Union[numpy.ndarray, List, torch.Tensor, warp.types.array]] = None) List[str]
Get effort modes for articulations in the view
- Parameters
indices (Optional[Union[np.ndarray, List, torch.Tensor, wp.array]], optional) – indices to specify which prims to query. Shape (M,). Where M <= size of the encapsulated prims in the view. Defaults to None (i.e: all prims in the view).
joint_indices (Optional[Union[np.ndarray, List, torch.Tensor, wp.array]], optional) – joint indices to specify which joints to query. Shape (K,). Where K <= num of dofs. Defaults to None (i.e: all dofs).
- Returns
Returns a List of size (M, K) indicating the effort modes:
accelerationorforce- Return type
List
Example:
>>> # get the effort mode for all joints >>> prims.get_effort_modes() [['acceleration', 'acceleration', 'acceleration', 'acceleration', 'acceleration', 'acceleration', 'acceleration', 'acceleration', 'acceleration'], ['acceleration', 'acceleration', 'acceleration', 'acceleration', 'acceleration', 'acceleration', 'acceleration', 'acceleration', 'acceleration'], ['acceleration', 'acceleration', 'acceleration', 'acceleration', 'acceleration', 'acceleration', 'acceleration', 'acceleration', 'acceleration'], ['acceleration', 'acceleration', 'acceleration', 'acceleration', 'acceleration', 'acceleration', 'acceleration', 'acceleration', 'acceleration'], ['acceleration', 'acceleration', 'acceleration', 'acceleration', 'acceleration', 'acceleration', 'acceleration', 'acceleration', 'acceleration']] >>> >>> # get only the finger joints effort modes for the first, middle and last of the 5 envs >>> prims.get_effort_modes(indices=np.array([0, 2, 4]), joint_indices=np.array([7, 8])) [['acceleration', 'acceleration'], ['acceleration', 'acceleration'], ['acceleration', 'acceleration']]
- get_enabled_self_collisions(indices: Optional[Union[numpy.ndarray, List, torch.Tensor, warp.types.array]] = None) Union[numpy.ndarray, torch.Tensor, warp.types.indexedarray]
Get the enable self collisions flag (
physxArticulation:enabledSelfCollisions) for all articulations- Parameters
indices (Optional[Union[np.ndarray, List, torch.Tensor, wp.array]], optional) – indices to specify which prims to query. Shape (M,). Where M <= size of the encapsulated prims in the view. Defaults to None (i.e: all prims in the view).
- Returns
self collisions flags (boolean interpreted as int). shape (M,)
- Return type
Union[np.ndarray, torch.Tensor, wp.indexedarray]
Example:
>>> # get all self collisions flags. Returned shape is (5,) for the example: 5 envs >>> prims.get_enabled_self_collisions() [0 0 0 0 0] >>> >>> # get the self collisions flags for the first, middle and last of the 5 envs. Returned shape is (3,) >>> prims.get_enabled_self_collisions(indices=np.array([0, 2, 4])) [0 0 0]
- get_fixed_tendon_dampings(indices: Optional[Union[numpy.ndarray, List, torch.Tensor, warp.types.array]] = None, clone: bool = True) Union[numpy.ndarray, torch.Tensor, warp.types.indexedarray]
Get the dampings of fixed tendons for articulations in the view
Search for Fixed Tendon in PhysX docs for more details
- Parameters
indices (Optional[Union[np.ndarray, List, torch.Tensor, wp.array]], optional) – indices to specify which prims to query. Shape (M,). Where M <= size of the encapsulated prims in the view. Defaults to None (i.e: all prims in the view).
clone (bool, optional) – True to return a clone of the internal buffer. Otherwise False. Defaults to True.
- Returns
fixed tendon dampings of articulations in the view. Shape is (M, K).
- Return type
Union[np.ndarray, torch.Tensor, wp.indexedarray]
Example:
>>> # get the fixed tendon dampings >>> # for the ShadowHand articulation that has 4 fixed tendons (prims.num_fixed_tendons) >>> prims.get_fixed_tendon_dampings() [[0. 0. 0. 0.] [0. 0. 0. 0.] [0. 0. 0. 0.] [0. 0. 0. 0.] [0. 0. 0. 0.]]
- get_fixed_tendon_limit_stiffnesses(indices: Optional[Union[numpy.ndarray, List, torch.Tensor, warp.types.array]] = None, clone: bool = True) Union[numpy.ndarray, torch.Tensor, warp.types.indexedarray]
Get the limit stiffness of fixed tendons for articulations in the view
Search for Fixed Tendon in PhysX docs for more details
- Parameters
indices (Optional[Union[np.ndarray, List, torch.Tensor, wp.array]], optional) – indices to specify which prims to query. Shape (M,). Where M <= size of the encapsulated prims in the view. Defaults to None (i.e: all prims in the view).
clone (bool, optional) – True to return a clone of the internal buffer. Otherwise False. Defaults to True.
- Returns
fixed tendon stiffnesses of articulations in the view. Shape is (M, K).
- Return type
Union[np.ndarray, torch.Tensor, wp.indexedarray]
Example:
>>> # get the fixed tendon limit stiffnesses >>> # for the ShadowHand articulation that has 4 fixed tendons (prims.num_fixed_tendons) >>> prims.get_fixed_tendon_limit_stiffnesses() [[0. 0. 0. 0.] [0. 0. 0. 0.] [0. 0. 0. 0.] [0. 0. 0. 0.] [0. 0. 0. 0.]]
- get_fixed_tendon_limits(indices: Optional[Union[numpy.ndarray, List, torch.Tensor, warp.types.array]] = None, clone: bool = True) Union[numpy.ndarray, torch.Tensor, warp.types.indexedarray]
Get the limits of fixed tendons for articulations in the view
Search for Fixed Tendon in PhysX docs for more details
- Parameters
indices (Optional[Union[np.ndarray, List, torch.Tensor, wp.array]], optional) – indices to specify which prims to query. Shape (M,). Where M <= size of the encapsulated prims in the view. Defaults to None (i.e: all prims in the view).
clone (bool, optional) – True to return a clone of the internal buffer. Otherwise False. Defaults to True.
- Returns
fixed tendon stiffnesses of articulations in the view. Shape is (M, K, 2).
- Return type
Union[np.ndarray, torch.Tensor, wp.indexedarray]
Example:
>>> # get the fixed tendon limits >>> # for the ShadowHand articulation that has 4 fixed tendons (prims.num_fixed_tendons) >>> prims.get_fixed_tendon_limits() [[[-0.001 0.001] [-0.001 0.001] [-0.001 0.001] [-0.001 0.001]] [[-0.001 0.001] [-0.001 0.001] [-0.001 0.001] [-0.001 0.001]] [[-0.001 0.001] [-0.001 0.001] [-0.001 0.001] [-0.001 0.001]] [[-0.001 0.001] [-0.001 0.001] [-0.001 0.001] [-0.001 0.001]] [[-0.001 0.001] [-0.001 0.001] [-0.001 0.001] [-0.001 0.001]]]
- get_fixed_tendon_offsets(indices: Optional[Union[numpy.ndarray, List, torch.Tensor, warp.types.array]] = None, clone: bool = True) Union[numpy.ndarray, torch.Tensor, warp.types.indexedarray]
Get the offsets of fixed tendons for articulations in the view
Search for Fixed Tendon in PhysX docs for more details
- Parameters
indices (Optional[Union[np.ndarray, List, torch.Tensor, wp.array]], optional) – indices to specify which prims to query. Shape (M,). Where M <= size of the encapsulated prims in the view. Defaults to None (i.e: all prims in the view).
clone (bool, optional) – True to return a clone of the internal buffer. Otherwise False. Defaults to True.
- Returns
fixed tendon stiffnesses of articulations in the view. Shape is (M, K).
- Return type
Union[np.ndarray, torch.Tensor, wp.indexedarray]
Example:
>>> # get the fixed tendon offsets >>> # for the ShadowHand articulation that has 4 fixed tendons (prims.num_fixed_tendons) >>> prims.get_fixed_tendon_offsets() [[0. 0. 0. 0.] [0. 0. 0. 0.] [0. 0. 0. 0.] [0. 0. 0. 0.] [0. 0. 0. 0.]]
- get_fixed_tendon_rest_lengths(indices: Optional[Union[numpy.ndarray, List, torch.Tensor, warp.types.array]] = None, clone: bool = True) Union[numpy.ndarray, torch.Tensor, warp.types.indexedarray]
Get the rest length of fixed tendons for articulations in the view
Search for Fixed Tendon in PhysX docs for more details
- Parameters
indices (Optional[Union[np.ndarray, List, torch.Tensor, wp.array]], optional) – indices to specify which prims to query. Shape (M,). Where M <= size of the encapsulated prims in the view. Defaults to None (i.e: all prims in the view).
clone (bool, optional) – True to return a clone of the internal buffer. Otherwise False. Defaults to True.
- Returns
fixed tendon stiffnesses of articulations in the view. Shape is (M, K).
- Return type
Union[np.ndarray, torch.Tensor, wp.indexedarray]
Example:
>>> # get the fixed tendon rest lengths >>> # for the ShadowHand articulation that has 4 fixed tendons (prims.num_fixed_tendons) >>> prims.get_fixed_tendon_rest_lengths() [[0. 0. 0. 0.] [0. 0. 0. 0.] [0. 0. 0. 0.] [0. 0. 0. 0.] [0. 0. 0. 0.]]
- get_fixed_tendon_stiffnesses(indices: Optional[Union[numpy.ndarray, List, torch.Tensor, warp.types.array]] = None, clone: bool = True) Union[numpy.ndarray, torch.Tensor, warp.types.indexedarray]
Get the stiffness of fixed tendons for articulations in the view
Search for Fixed Tendon in PhysX docs for more details
- Parameters
indices (Optional[Union[np.ndarray, List, torch.Tensor, wp.array]], optional) – indices to specify which prims to query. Shape (M,). Where M <= size of the encapsulated prims in the view. Defaults to None (i.e: all prims in the view).
clone (bool, optional) – True to return a clone of the internal buffer. Otherwise False. Defaults to True.
- Returns
fixed tendon stiffnesses of articulations in the view. Shape is (M, K).
- Return type
Union[np.ndarray, torch.Tensor, wp.indexedarray]
Example:
>>> # get the fixed tendon stiffnesses >>> # for the ShadowHand articulation that has 4 fixed tendons (prims.num_fixed_tendons) >>> prims.get_fixed_tendon_stiffnesses() [[0. 0. 0. 0.] [0. 0. 0. 0.] [0. 0. 0. 0.] [0. 0. 0. 0.] [0. 0. 0. 0.]]
- get_friction_coefficients(indices: Optional[Union[numpy.ndarray, List, torch.Tensor, warp.types.array]] = None, joint_indices: Optional[Union[numpy.ndarray, List, torch.Tensor, warp.types.array]] = None, clone: bool = True) Union[numpy.ndarray, torch.Tensor, warp.types.array]
Get the friction coefficients for the articulation joints in the view
Search for “Joint Friction Coefficient” in PhysX docs for more details.
- Parameters
indices (Optional[Union[np.ndarray, List, torch.Tensor, wp.array]], optional) – indices to specify which prims to query. Shape (M,). Where M <= size of the encapsulated prims in the view. Defaults to None (i.e: all prims in the view).
joint_indices (Optional[Union[np.ndarray, List, torch.Tensor, wp.array]], optional) – joint indices to specify which joints to query. Shape (K,). Where K <= num of dofs. Defaults to None (i.e: all dofs).
clone (Optional[bool]) – True to return a clone of the internal buffer. Otherwise False. Defaults to True.
- Returns
joint friction coefficients for articulations in the view. shape (M, K).
- Return type
Union[np.ndarray, torch.Tensor, wp.indexedarray]
Example:
>>> # get joint friction coefficients. Returned shape is (5, 9) for the example: 5 envs, 9 DOFs >>> prims.get_friction_coefficients() [[0. 0. 0. 0. 0. 0. 0. 0. 0.] [0. 0. 0. 0. 0. 0. 0. 0. 0.] [0. 0. 0. 0. 0. 0. 0. 0. 0.] [0. 0. 0. 0. 0. 0. 0. 0. 0.] [0. 0. 0. 0. 0. 0. 0. 0. 0.]] >>> >>> # get only the finger joint (panda_finger_joint1 (7) and panda_finger_joint2 (8)) friction coefficients >>> # for the first, middle and last of the 5 envs. Returned shape is (3, 2) >>> prims.get_friction_coefficients(indices=np.array([0,2,4]), joint_indices=np.array([7,8])) [[0. 0.] [0. 0.] [0. 0.]]
- get_gains(indices: Optional[Union[numpy.ndarray, List, torch.Tensor, warp.types.array]] = None, joint_indices: Optional[Union[numpy.ndarray, List, torch.Tensor, warp.types.array]] = None, clone: bool = True) Tuple[typing.Union[numpy.ndarray, torch.Tensor], typing.Union[numpy.ndarray, torch.Tensor], typing.Union[warp.types.indexedarray, <Function index(a: vector(length=2, dtype=<class 'warp.types.float16'>), i: int32)>]]
Get the implicit Proportional-Derivative (PD) controller’s Kps (stiffnesses) and Kds (dampings) of articulations in the view
- Parameters
indices (Optional[Union[np.ndarray, List, torch.Tensor, wp.array]], optional) – indices to specify which prims to query. Shape (M,). Where M <= size of the encapsulated prims in the view. Defaults to None (i.e: all prims in the view).
joint_indices (Optional[Union[np.ndarray, List, torch.Tensor, wp.array]], optional) – joint indices to specify which joints to query. Shape (K,). Where K <= num of dofs. Defaults to None (i.e: all dofs).
clone (bool, optional) – True to return clones of the internal buffers. Otherwise False. Defaults to True.
- Returns
stiffness and damping of articulations in the view respectively. shapes are (M, K).
- Return type
Tuple[Union[np.ndarray, torch.Tensor], Union[np.ndarray, torch.Tensor], Union[wp.indexedarray, wp.index]]
Example:
>>> # get all joint stiffness and damping. Returned shape is (5, 9) for the example: 5 envs, 9 DOFs >>> stiffnesses, dampings = prims.get_gains() >>> stiffnesses [[60000. 60000. 60000. 60000. 25000. 15000. 5000. 6000. 6000.] [60000. 60000. 60000. 60000. 25000. 15000. 5000. 6000. 6000.] [60000. 60000. 60000. 60000. 25000. 15000. 5000. 6000. 6000.] [60000. 60000. 60000. 60000. 25000. 15000. 5000. 6000. 6000.] [60000. 60000. 60000. 60000. 25000. 15000. 5000. 6000. 6000.]] >>> dampings [[3000. 3000. 3000. 3000. 3000. 3000. 3000. 1000. 1000.] [3000. 3000. 3000. 3000. 3000. 3000. 3000. 1000. 1000.] [3000. 3000. 3000. 3000. 3000. 3000. 3000. 1000. 1000.] [3000. 3000. 3000. 3000. 3000. 3000. 3000. 1000. 1000.] [3000. 3000. 3000. 3000. 3000. 3000. 3000. 1000. 1000.]] >>> >>> # get finger joints stiffness and damping: panda_finger_joint1 (7) and panda_finger_joint2 (8) >>> # for the first, middle and last of the 5 envs. Returned shape is (3, 2) >>> stiffnesses, dampings = prims.get_gains(indices=np.array([0, 2, 4]), joint_indices=np.array([7, 8])) >>> stiffnesses [[6000. 6000.] [6000. 6000.] [6000. 6000.]] >>> dampings [[1000. 1000.] [1000. 1000.] [1000. 1000.]]
- get_generalized_gravity_forces(indices: Optional[Union[numpy.ndarray, List, torch.Tensor, warp.types.array]] = None, joint_indices: Optional[Union[numpy.ndarray, List, torch.Tensor, warp.types.array]] = None, clone: bool = True) Union[numpy.ndarray, torch.Tensor, warp.types.indexedarray]
Get the generalized gravity forces (joint DOF forces required to counteract gravitational forces for the given articulation pose) of articulations in the view
Search for Generalized Gravity Force in PhysX docs for more details
- Parameters
indices (Optional[Union[np.ndarray, List, torch.Tensor, wp.array]], optional) – indices to specify which prims to query. Shape (M,). Where M <= size of the encapsulated prims in the view. Defaults to None (i.e: all prims in the view).
joint_indices (Optional[Union[np.ndarray, List, torch.Tensor, wp.array]], optional) – joint indices to specify which joints to query. Shape (K,). Where K <= num of dofs. Defaults to None (i.e: all dofs).
clone (bool, optional) – True to return a clone of the internal buffer. Otherwise False. Defaults to True.
- Returns
generalized gravity forces of articulations in the view. Shape is (M, K).
- Return type
Union[np.ndarray, torch.Tensor, wp.indexedarray]
Example:
>>> >>> # get all generalized gravity forces. Returned shape is (5, 9) for the example: 5 envs, 9 DOFs >>> prims.get_generalized_gravity_forces() [[ 1.32438602e-08 -6.90832138e+00 -1.08629465e-05 1.91585541e+01 5.13810664e-06 1.18674076e+00 8.01788883e-06 5.18786255e-03 -5.18784765e-03] [ 1.32438602e-08 -6.90832138e+00 -1.08629465e-05 1.91585541e+01 5.13810664e-06 1.18674076e+00 8.01788883e-06 5.18786255e-03 -5.18784765e-03] [ 1.32438585e-08 -6.90830994e+00 -1.08778477e-05 1.91585541e+01 5.14090061e-06 1.18674052e+00 8.02161412e-06 5.18786255e-03 -5.18784765e-03] [ 1.32438585e-08 -6.90830994e+00 -1.08778477e-05 1.91585541e+01 5.14090061e-06 1.18674052e+00 8.02161412e-06 5.18786255e-03 -5.18784765e-03] [ 1.32438602e-08 -6.90832138e+00 -1.08629465e-05 1.91585541e+01 5.13810664e-06 1.18674076e+00 8.01788883e-06 5.18786255e-03 -5.18784765e-03]] >>> >>> # get finger joint generalized gravity forces: panda_finger_joint1 (7) and panda_finger_joint2 (8) >>> # for the first, middle and last of the 5 envs. Returned shape is (3, 2) >>> prims.get_generalized_gravity_forces(indices=np.array([0, 2, 4]), joint_indices=np.array([7, 8])) [[ 0.00518786 -0.00518785] [ 0.00518786 -0.00518785] [ 0.00518786 -0.00518785]]
- get_jacobian_shape() Union[numpy.ndarray, torch.Tensor, warp.types.array]
Get the Jacobian matrix shape of a single articulation
The Jacobian matrix maps the joint space velocities of a DOF to it’s cartesian and angular velocities
The shape of the Jacobian depends on the number of links (rigid bodies), DOFs, and whether the articulation base is fixed (e.g., robotic manipulators) or not (e.g,. mobile robots).
Fixed articulation base:
(num_bodies - 1, 6, num_dof)Non-fixed articulation base:
(num_bodies, 6, num_dof + 6)
Each body has 6 values in the Jacobian representing its linear and angular motion along the three coordinate axes. The extra 6 DOFs in the last dimension, for non-fixed base cases, correspond to the linear and angular degrees of freedom of the free root link
- Returns
shape of jacobian for a single articulation.
- Return type
Union[np.ndarray, torch.Tensor, wp.array]
Example:
>>> # for the Franka Panda (a robotic manipulator with fixed base): >>> # - num_bodies: 12 >>> # - num_dof: 9 >>> prims.get_jacobian_shape() (11, 6, 9)
- get_jacobians(indices: Optional[Union[numpy.ndarray, List, torch.Tensor, warp.types.array]] = None, clone: bool = True) Union[numpy.ndarray, torch.Tensor, warp.types.indexedarray]
Get the Jacobian matrices of articulations in the view
Note
The first dimension corresponds to the amount of wrapped articulations while the last 3 dimensions are the Jacobian matrix shape. Refer to the
get_jacobian_shapemethod for details about the Jacobian matrix shape- Parameters
indices (Optional[Union[np.ndarray, List, torch.Tensor, wp.array]], optional) – indices to specify which prims to query. Shape (M,). Where M <= size of the encapsulated prims in the view. Defaults to None (i.e: all prims in the view).
clone (bool, optional) – True to return a clone of the internal buffer. Otherwise False. Defaults to True.
- Returns
Jacobian matrices of articulations in the view. Shape is (M, jacobian_shape).
- Return type
Union[np.ndarray, torch.Tensor, wp.indexedarray]
Example:
>>> # get the Jacobian matrices. Returned shape is (5, 11, 6, 9) for the example: 5 envs, 12 links, 9 DOFs >>> prims.get_jacobians() [[[[ 4.2254178e-09 0.0000000e+00 0.0000000e+00 ... 0.0000000e+00 0.0000000e+00 0.0000000e+00] [ 1.2093576e-08 0.0000000e+00 0.0000000e+00 ... 0.0000000e+00 0.0000000e+00 0.0000000e+00] [-6.0873992e-16 0.0000000e+00 0.0000000e+00 ... 0.0000000e+00 0.0000000e+00 0.0000000e+00] [ 1.4458647e-07 0.0000000e+00 0.0000000e+00 ... 0.0000000e+00 0.0000000e+00 0.0000000e+00] [-1.8178657e-10 0.0000000e+00 0.0000000e+00 ... 0.0000000e+00 0.0000000e+00 0.0000000e+00] [ 9.9999976e-01 0.0000000e+00 0.0000000e+00 ... 0.0000000e+00 0.0000000e+00 0.0000000e+00]] ... [[-4.5089945e-02 8.1210062e-02 -3.8495898e-02 ... 2.8108317e-02 0.0000000e+00 -4.9317405e-02] [ 4.2863289e-01 9.7436900e-04 4.0475106e-01 ... 2.4577195e-03 0.0000000e+00 9.9807423e-01] [ 6.5973169e-09 -4.2914307e-01 -2.1542320e-02 ... 2.8352857e-02 0.0000000e+00 -3.7625343e-02] [ 1.4458647e-07 -1.1999309e-02 -5.3927803e-01 ... 7.0976764e-01 0.0000000e+00 0.0000000e+00] [-1.8178657e-10 9.9992776e-01 -6.4710006e-03 ... 8.5178167e-03 0.0000000e+00 0.0000000e+00] [ 9.9999976e-01 -3.8743019e-07 8.4210289e-01 ... -7.0438433e-01 0.0000000e+00 0.0000000e+00]]]]
- get_joint_index(joint_name: str) int
Get a joint index in the joint buffers given its name
- Parameters
joint_name (str) – name of the joint that corresponds to the index of the joint in the articulation
- Returns
index of the joint in the joint buffers
- Return type
int
- get_joint_max_velocities(indices: Optional[Union[numpy.ndarray, List, torch.Tensor, warp.types.array]] = None, joint_indices: Optional[Union[numpy.ndarray, List, torch.Tensor, warp.types.array]] = None, clone: bool = True) Union[numpy.ndarray, torch.Tensor, warp.types.indexedarray]
Get the maximum joint velocities for articulation dofs in the view
- Parameters
indices (Optional[Union[np.ndarray, List, torch.Tensor, wp.array]], optional) – indices to specify which prims to query. Shape (M,). Where M <= size of the encapsulated prims in the view. Defaults to None (i.e: all prims in the view).
joint_indices (Optional[Union[np.ndarray, List, torch.Tensor, wp.array]], optional) – joint indices to specify which joints to query. Shape (K,). Where K <= num of dofs. Defaults to None (i.e: all dofs).
clone (Optional[bool]) – True to return a clone of the internal buffer. Otherwise False. Defaults to True.
- Returns
maximum joint velocities for articulations dofs in the view. shape (M, K).
- Return type
Union[np.ndarray, torch.Tensor, wp.indexedarray]
- get_joint_positions(indices: Optional[Union[numpy.ndarray, List, torch.Tensor, warp.types.array]] = None, joint_indices: Optional[Union[numpy.ndarray, List, torch.Tensor, warp.types.array]] = None, clone: bool = True) Union[numpy.ndarray, torch.Tensor, warp.types.indexedarray]
Get the joint positions of articulations in the view
- Parameters
indices (Optional[Union[np.ndarray, List, torch.Tensor, wp.array]], optional) – indices to specify which prims to query. Shape (M,). Where M <= size of the encapsulated prims in the view. Defaults to None (i.e: all prims in the view).
joint_indices (Optional[Union[np.ndarray, List, torch.Tensor, wp.array]], optional) – joint indices to specify which joints to query. Shape (K,). Where K <= num of dofs. Defaults to None (i.e: all dofs).
clone (bool, optional) – True to return a clone of the internal buffer. Otherwise False. Defaults to True.
- Returns
joint positions of articulations in the view. Shape is (M, K).
- Return type
Union[np.ndarray, torch.Tensor, wp.indexedarray]
Example:
>>> # get all joint positions. Returned shape is (5, 9) for the example: 5 envs, 9 DOFs >>> prims.get_joint_positions() [[ 1.1999921e-02 -5.6962633e-01 1.3219320e-08 -2.8105433e+00 6.8276213e-06 3.0301569e+00 7.3234755e-01 3.9912373e-02 3.9999999e-02] [ 1.1999921e-02 -5.6962633e-01 1.3219320e-08 -2.8105433e+00 6.8276213e-06 3.0301569e+00 7.3234755e-01 3.9912373e-02 3.9999999e-02] [ 1.1999921e-02 -5.6962633e-01 1.3220056e-08 -2.8105433e+00 6.8276104e-06 3.0301569e+00 7.3234755e-01 3.9912373e-02 3.9999999e-02] [ 1.1999921e-02 -5.6962633e-01 1.3220056e-08 -2.8105433e+00 6.8276104e-06 3.0301569e+00 7.3234755e-01 3.9912373e-02 3.9999999e-02] [ 1.1999921e-02 -5.6962633e-01 1.3219320e-08 -2.8105433e+00 6.8276213e-06 3.0301569e+00 7.3234755e-01 3.9912373e-02 3.9999999e-02]] >>> >>> # get finger joint positions: panda_finger_joint1 (7) and panda_finger_joint2 (8) >>> # for the first, middle and last of the 5 envs. Returned shape is (3, 2) >>> prims.get_joint_positions(indices=np.array([0, 2, 4]), joint_indices=np.array([7, 8])) [[0.03991237 0.04 ] [0.03991237 0.04 ] [0.03991237 0.04 ]]
- get_joint_velocities(indices: Optional[Union[numpy.ndarray, List, torch.Tensor, warp.types.array]] = None, joint_indices: Optional[Union[numpy.ndarray, List, torch.Tensor, warp.types.array]] = None, clone: bool = True) Union[numpy.ndarray, torch.Tensor, warp.types.indexedarray]
Get the joint velocities of articulations in the view
- Parameters
indices (Optional[Union[np.ndarray, List, torch.Tensor, wp.array]], optional) – indices to specify which prims to query. Shape (M,). Where M <= size of the encapsulated prims in the view. Defaults to None (i.e: all prims in the view).
joint_indices (Optional[Union[np.ndarray, List, torch.Tensor, wp.array]], optional) – joint indices to specify which joints to query. Shape (K,). Where K <= num of dofs. Defaults to None (i.e: all dofs).
clone (bool, optional) – True to return a clone of the internal buffer. Otherwise False. Defaults to True.
- Returns
joint velocities of articulations in the view. Shape is (M, K).
- Return type
Union[np.ndarray, torch.Tensor, wp.indexedarray]
Example:
>>> # get all joint velocities. Returned shape is (5, 9) for the example: 5 envs, 9 DOFs >>> prims.get_joint_velocities() [[ 1.9010375e-06 -7.6763844e-03 -2.1396865e-07 1.1063669e-02 -4.6333633e-05 3.4824573e-02 8.8469200e-02 5.4033857e-04 1.0287426e-05] [ 1.9010375e-06 -7.6763844e-03 -2.1396865e-07 1.1063669e-02 -4.6333633e-05 3.4824573e-02 8.8469200e-02 5.4033857e-04 1.0287426e-05] [ 1.9010074e-06 -7.6763779e-03 -2.1403629e-07 1.1063648e-02 -4.6333400e-05 3.4824558e-02 8.8469170e-02 5.4033566e-04 1.0287110e-05] [ 1.9010074e-06 -7.6763779e-03 -2.1403629e-07 1.1063648e-02 -4.6333400e-05 3.4824558e-02 8.8469170e-02 5.4033566e-04 1.0287110e-05] [ 1.9010375e-06 -7.6763844e-03 -2.1396865e-07 1.1063669e-02 -4.6333633e-05 3.4824573e-02 8.8469200e-02 5.4033857e-04 1.0287426e-05]] >>> >>> # get finger joint velocities: panda_finger_joint1 (7) and panda_finger_joint2 (8) >>> # for the first, middle and last of the 5 envs. Returned shape is (3, 2) >>> prims.get_joint_velocities(indices=np.array([0, 2, 4]), joint_indices=np.array([7, 8])) [[5.4033857e-04 1.0287426e-05] [5.4033566e-04 1.0287110e-05] [5.4033857e-04 1.0287426e-05]]
- get_joints_default_state() omni.isaac.core.utils.types.JointsState
Get the default joint states defined with the
set_joints_default_statemethod- Returns
an object that contains the default joint states
- Return type
Example:
>>> # returned shape is (5, 9) for the example: 5 envs, 9 DOFs >>> states = prims.get_joints_default_state() >>> states <omni.isaac.core.utils.types.JointsState object at 0x7fc2c174fd90> >>> states.positions [[ 0. -1. 0. -2.2 0. 2.4 0.8 0.04 0.04] [ 0. -1. 0. -2.2 0. 2.4 0.8 0.04 0.04] [ 0. -1. 0. -2.2 0. 2.4 0.8 0.04 0.04] [ 0. -1. 0. -2.2 0. 2.4 0.8 0.04 0.04] [ 0. -1. 0. -2.2 0. 2.4 0.8 0.04 0.04]] >>> states.velocities [[0. 0. 0. 0. 0. 0. 0. 0. 0.] [0. 0. 0. 0. 0. 0. 0. 0. 0.] [0. 0. 0. 0. 0. 0. 0. 0. 0.] [0. 0. 0. 0. 0. 0. 0. 0. 0.] [0. 0. 0. 0. 0. 0. 0. 0. 0.]] >>> states.efforts [[0. 0. 0. 0. 0. 0. 0. 0. 0.] [0. 0. 0. 0. 0. 0. 0. 0. 0.] [0. 0. 0. 0. 0. 0. 0. 0. 0.] [0. 0. 0. 0. 0. 0. 0. 0. 0.] [0. 0. 0. 0. 0. 0. 0. 0. 0.]]
- get_joints_state() omni.isaac.core.utils.types.JointsState
Get the current joint states (positions and velocities)
- Returns
an object that contains the current joint positions and velocities
- Return type
Example:
>>> # returned shape is (5, 9) for the example: 5 envs, 9 DOFs >>> states = prims.get_joints_state() >>> states <omni.isaac.core.utils.types.JointsState object at 0x7fc1a23a82e0> >>> states.positions [[ 1.1999921e-02 -5.6962633e-01 1.3219320e-08 -2.8105433e+00 6.8276213e-06 3.0301569e+00 7.3234755e-01 3.9912373e-02 3.9999999e-02] [ 1.1999921e-02 -5.6962633e-01 1.3219320e-08 -2.8105433e+00 6.8276213e-06 3.0301569e+00 7.3234755e-01 3.9912373e-02 3.9999999e-02] [ 1.1999921e-02 -5.6962633e-01 1.3220056e-08 -2.8105433e+00 6.8276104e-06 3.0301569e+00 7.3234755e-01 3.9912373e-02 3.9999999e-02] [ 1.1999921e-02 -5.6962633e-01 1.3220056e-08 -2.8105433e+00 6.8276104e-06 3.0301569e+00 7.3234755e-01 3.9912373e-02 3.9999999e-02] [ 1.1999921e-02 -5.6962633e-01 1.3219320e-08 -2.8105433e+00 6.8276213e-06 3.0301569e+00 7.3234755e-01 3.9912373e-02 3.9999999e-02]] >>> states.velocities [[ 1.9010375e-06 -7.6763844e-03 -2.1396865e-07 1.1063669e-02 -4.6333633e-05 3.4824573e-02 8.8469200e-02 5.4033857e-04 1.0287426e-05] [ 1.9010375e-06 -7.6763844e-03 -2.1396865e-07 1.1063669e-02 -4.6333633e-05 3.4824573e-02 8.8469200e-02 5.4033857e-04 1.0287426e-05] [ 1.9010074e-06 -7.6763779e-03 -2.1403629e-07 1.1063648e-02 -4.6333400e-05 3.4824558e-02 8.8469170e-02 5.4033566e-04 1.0287110e-05] [ 1.9010074e-06 -7.6763779e-03 -2.1403629e-07 1.1063648e-02 -4.6333400e-05 3.4824558e-02 8.8469170e-02 5.4033566e-04 1.0287110e-05] [ 1.9010375e-06 -7.6763844e-03 -2.1396865e-07 1.1063669e-02 -4.6333633e-05 3.4824573e-02 8.8469200e-02 5.4033857e-04 1.0287426e-05]]
- get_linear_velocities(indices: Optional[Union[numpy.ndarray, list, torch.Tensor, warp.types.array]] = None, clone=True) Union[numpy.ndarray, torch.Tensor, warp.types.indexedarray]
Get the linear velocities of prims in the view.
- Parameters
indices (Optional[Union[np.ndarray, list, torch.Tensor, wp.array]], optional) – indices to specify which prims to query. Shape (M,). Where M <= size of the encapsulated prims in the view. Defaults to None (i.e: all prims in the view)
clone (bool, optional) – True to return a clone of the internal buffer. Otherwise False. Defaults to True.
- Returns
linear velocities of the prims in the view. shape is (M, 3).
- Return type
Union[np.ndarray, torch.Tensor, wp.indexedarray]
Example:
>>> # get all articulation linear velocities. Returned shape is (5, 3) for the example: 5 envs, linear (3) >>> prims.get_linear_velocities() [[0. 0. 0.] [0. 0. 0.] [0. 0. 0.] [0. 0. 0.] [0. 0. 0.]] >>> >>> # get only the articulation linear velocities for the first, middle and last of the 5 envs. >>> # Returned shape is (3, 3) for the example: 3 envs selected, linear (3) >>> prims.get_linear_velocities(indices=np.array([0, 2, 4])) [[0. 0. 0.] [0. 0. 0.] [0. 0. 0.]]
- get_link_index(link_name: str) int
Get a link index in the link buffers given its name
- Parameters
link_name (str) – name of the link that corresponds to the index of the link in the articulation
- Returns
index of the link in the link buffers
- Return type
int
- get_local_poses(indices: Optional[Union[numpy.ndarray, list, torch.Tensor, warp.types.array]] = None) Union[Tuple[numpy.ndarray, numpy.ndarray], Tuple[torch.Tensor, torch.Tensor], Tuple[warp.types.indexedarray, warp.types.indexedarray]]
Get prim poses in the view with respect to the local frame (the prim’s parent frame).
- Parameters
indices (Optional[Union[np.ndarray, list, torch.Tensor, wp.array]], optional) – indices to specify which prims to query. Shape (M,). Where M <= size of the encapsulated prims in the view. Defaults to None (i.e: all prims in the view)
- Returns
first index is positions in the local frame of the prims. shape is (M, 3). Second index is quaternion orientations in the local frame of the prims. Quaternion is scalar-first (w, x, y, z). shape is (M, 4).
- Return type
Union[Tuple[np.ndarray, np.ndarray], Tuple[torch.Tensor, torch.Tensor], Tuple[wp.indexedarray, wp.indexedarray]]
Example:
>>> # get all articulation poses with respect to the local frame. >>> # Returned shape is position (5, 3) and orientation (5, 4) for the example: 5 envs >>> positions, orientations = prims.get_local_poses() >>> positions [[ 0.0000000e+00 0.0000000e+00 -2.8610229e-08] [ 0.0000000e+00 0.0000000e+00 -2.8610229e-08] [-4.5299529e-08 0.0000000e+00 -2.8610229e-08] [-4.5299529e-08 0.0000000e+00 -2.8610229e-08] [ 0.0000000e+00 0.0000000e+00 -2.8610229e-08]] >>> orientations [[1. 0. 0. 0.] [1. 0. 0. 0.] [1. 0. 0. 0.] [1. 0. 0. 0.] [1. 0. 0. 0.]] >>> >>> # get only the articulation poses with respect to the local frame for the first, middle and last of the 5 envs. >>> # Returned shape is position (3, 3) and orientation (3, 4) for the example: 3 envs selected >>> positions, orientations = prims.get_local_poses(indices=np.array([0, 2, 4])) >>> positions [[ 0.0000000e+00 0.0000000e+00 -2.8610229e-08] [-4.5299529e-08 0.0000000e+00 -2.8610229e-08] [ 0.0000000e+00 0.0000000e+00 -2.8610229e-08]] >>> orientations [[1. 0. 0. 0.] [1. 0. 0. 0.] [1. 0. 0. 0.]]
- get_local_scales(indices: Optional[Union[numpy.ndarray, list, torch.Tensor, warp.types.array]] = None) Union[numpy.ndarray, torch.Tensor, warp.types.indexedarray]
Get prim scales in the view with respect to the local frame (the parent’s frame).
- Parameters
indices (Optional[Union[np.ndarray, list, torch.Tensor, wp.array]], optional) – indices to specify which prims to query. Shape (M,). Where M <= size of the encapsulated prims in the view. Defaults to None (i.e: all prims in the view).
- Returns
scales applied to the prim’s dimensions in the local frame. shape is (M, 3).
- Return type
Union[np.ndarray, torch.Tensor, wp.indexedarray]
Example:
>>> # get all prims scales with respect to the local frame. >>> # Returned shape is (5, 3) for the example: 5 envs >>> prims.get_local_scales() [[1. 1. 1.] [1. 1. 1.] [1. 1. 1.] [1. 1. 1.] [1. 1. 1.]] >>> >>> # get only the prims scales with respect to the local frame for the first, middle and last of the 5 envs. >>> # Returned shape is (3, 3) for the example: 3 envs selected >>> prims.get_local_scales(indices=np.array([0, 2, 4])) [[1. 1. 1.] [1. 1. 1.] [1. 1. 1.]]
- get_mass_matrices(indices: Optional[Union[numpy.ndarray, List, torch.Tensor, warp.types.array]] = None, clone: bool = True) Union[numpy.ndarray, torch.Tensor, warp.types.indexedarray]
Get the mass matrices of articulations in the view
Note
The first dimension corresponds to the amount of wrapped articulations while the last 2 dimensions are the mass matrix shape. Refer to the
get_mass_matrix_shapemethod for details about the mass matrix shape- Parameters
indices (Optional[Union[np.ndarray, List, torch.Tensor, wp.array]], optional) – indices to specify which prims to query. Shape (M,). Where M <= size of the encapsulated prims in the view. Defaults to None (i.e: all prims in the view).
clone (bool, optional) – True to return a clone of the internal buffer. Otherwise False. Defaults to True.
- Returns
mass matrices of articulations in the view. Shape is (M, mass_matrix_shape).
- Return type
Union[np.ndarray, torch.Tensor, wp.indexedarray]
Example:
>>> # get the mass matrices. Returned shape is (5, 9, 9) for the example: 5 envs, 9 DOFs >>> prims.get_mass_matrices() [[[ 5.0900602e-01 1.1794259e-06 4.2570841e-01 -1.6387942e-06 -3.1573933e-02 -1.9736715e-06 -3.1358242e-04 -6.0441834e-03 6.0441834e-03] [ 1.1794259e-06 1.0598221e+00 7.4729815e-07 -4.2621672e-01 2.3612277e-08 -4.9647894e-02 -2.9080724e-07 -1.8432185e-04 1.8432130e-04] ... [-6.0441834e-03 -1.8432185e-04 -5.7159867e-03 4.0070520e-04 9.6930371e-04 1.2324301e-04 2.5264668e-10 1.4055224e-02 0.0000000e+00] [ 6.0441834e-03 1.8432130e-04 5.7159867e-03 -4.0070404e-04 -9.6930366e-04 -1.2324269e-04 -3.6906206e-10 0.0000000e+00 1.4055224e-02]]]
- get_mass_matrix_shape() Union[numpy.ndarray, torch.Tensor, warp.types.array]
Get the mass matrix shape of a single articulation
The mass matrix contains the generalized mass of the robot depending on the current configuration
The shape of the max matrix depends on the number of DOFs:
(num_dof, num_dof)- Returns
shape of mass matrix for a single articulation.
- Return type
Union[np.ndarray, torch.Tensor, wp.array]
Example:
>>> # for the Franka Panda: >>> # - num_dof: 9 >>> prims.get_jacobian_shape() (9, 9)
- get_max_efforts(indices: Optional[Union[numpy.ndarray, List, torch.Tensor, warp.types.array]] = None, joint_indices: Optional[Union[numpy.ndarray, List, torch.Tensor, warp.types.array]] = None, clone: bool = True) Union[numpy.ndarray, torch.Tensor, warp.types.indexedarray]
Get the maximum efforts for articulation in the view
- Parameters
indices (Optional[Union[np.ndarray, List, torch.Tensor, wp.array]], optional) – indices to specify which prims to query. Shape (M,). Where M <= size of the encapsulated prims in the view. Defaults to None (i.e: all prims in the view).
joint_indices (Optional[Union[np.ndarray, List, torch.Tensor, wp.array]], optional) – joint indices to specify which joints to query. Shape (K,). Where K <= num of dofs. Defaults to None (i.e: all dofs).
clone (Optional[bool]) – True to return a clone of the internal buffer. Otherwise False. Defaults to True.
- Returns
maximum efforts for articulations in the view. shape (M, K).
- Return type
Union[np.ndarray, torch.Tensor, wp.indexedarray]
Example:
>>> # get all joint maximum efforts. Returned shape is (5, 9) for the example: 5 envs, 9 DOFs >>> prims.get_max_efforts() [[5220. 5220. 5220. 5220. 720. 720. 720. 720. 720.] [5220. 5220. 5220. 5220. 720. 720. 720. 720. 720.] [5220. 5220. 5220. 5220. 720. 720. 720. 720. 720.] [5220. 5220. 5220. 5220. 720. 720. 720. 720. 720.] [5220. 5220. 5220. 5220. 720. 720. 720. 720. 720.]] >>> >>> # get finger joint maximum efforts: panda_finger_joint1 (7) and panda_finger_joint2 (8) >>> # for the first, middle and last of the 5 envs. Returned shape is (3, 2) >>> prims.get_max_efforts(indices=np.array([0, 2, 4]), joint_indices=np.array([7, 8])) [[720. 720.] [720. 720.] [720. 720.]]
- get_measured_joint_efforts(indices: Optional[Union[numpy.ndarray, List, torch.Tensor, warp.types.array]] = None, joint_indices: Optional[Union[numpy.ndarray, List, torch.Tensor, warp.types.array]] = None, clone: bool = True) Union[numpy.ndarray, torch.Tensor, warp.types.indexedarray]
Returns the efforts computed/measured by the physics solver of the joint forces in the DOF motion direction
- Parameters
indices (Optional[Union[np.ndarray, List, torch.Tensor]], optional) – indices to specify which prims to query. Shape (M,). Where M <= size of the encapsulated prims in the view. Defaults to None (i.e: all prims in the view).
joint_indices (Optional[Union[np.ndarray, List, torch.Tensor]], optional) – joint indices to specify which joints to query. Shape (K,). Where K <= num of dofs. Defaults to None (i.e: all dofs).
clone (bool, optional) – True to return a clone of the internal buffer. Otherwise False. Defaults to True.
- Returns
computed joint efforts of articulations in the view. shape is (M, K).
- Return type
Union[np.ndarray, torch.Tensor]
Example:
>>> # get all measured joint efforts. Returned shape is (5, 9) for the example: 5 envs, 9 DOFs >>> prims.get_measured_joint_efforts() [[ 4.8250298e-05 -6.9073005e+00 5.3364405e-05 1.9157070e+01 -5.8759182e-05 1.1863427e+00 -5.6388220e-05 5.1680300e-03 -5.1910817e-03] [ 4.8250298e-05 -6.9073005e+00 5.3364405e-05 1.9157070e+01 -5.8759182e-05 1.1863427e+00 -5.6388220e-05 5.1680300e-03 -5.1910817e-03] [ 4.8254540e-05 -6.9072919e+00 5.3344327e-05 1.9157072e+01 -5.8761045e-05 1.1863427e+00 -5.6405144e-05 5.1680212e-03 -5.1910840e-03] [ 4.8254540e-05 -6.9072919e+00 5.3344327e-05 1.9157072e+01 -5.8761045e-05 1.1863427e+00 -5.6405144e-05 5.1680212e-03 -5.1910840e-03] [ 4.8250298e-05 -6.9073005e+00 5.3364405e-05 1.9157070e+01 -5.8759182e-05 1.1863427e+00 -5.6388220e-05 5.1680300e-03 -5.1910817e-03]] >>> >>> # get finger measured joint efforts: panda_finger_joint1 (7) and panda_finger_joint2 (8) >>> # for the first, middle and last of the 5 envs. Returned shape is (3, 2) >>> prims.get_measured_joint_efforts(indices=np.array([0, 2, 4]), joint_indices=np.array([7, 8])) [[ 0.00516803 -0.00519108] [ 0.00516802 -0.00519108] [ 0.00516803 -0.00519108]]
- get_measured_joint_forces(indices: Optional[Union[numpy.ndarray, List, torch.Tensor]] = None, joint_indices: Optional[Union[numpy.ndarray, List, torch.Tensor]] = None, clone: bool = True) Union[numpy.ndarray, torch.Tensor]
Get the measured joint reaction forces and torques (link incoming joint forces and torques) to external loads
Note
Since the name->index map for joints has not been exposed yet, it is possible to access the joint names and their indices through the articulation metadata.
prims._metadata.joint_names # list of names prims._metadata.joint_indices # dict of name: index
To retrieve a specific row for the link incoming joint force/torque use
joint_index + 1- Parameters
indices (Optional[Union[np.ndarray, List, torch.Tensor]], optional) – indices to specify which prims to query. Shape (M,). Where M <= size of the encapsulated prims in the view. Defaults to None (i.e: all prims in the view).
joint_indices (Optional[Union[np.ndarray, List, torch.Tensor]], optional) – link indices to specify which link’s incoming joints to query. Shape (K,). Where K <= num of links/bodies. Defaults to None (i.e: all dofs).
clone (bool, optional) – True to return a clone of the internal buffer. Otherwise False. Defaults to True.
- Returns
joint forces and torques of articulations in the view. Shape is (M, num_joint + 1, 6). Column index 0 is the incoming joint of the base link. For the last dimension the first 3 values are for forces and the last 3 for torques
- Return type
Union[np.ndarray, torch.Tensor]
Example:
>>> # get all measured joint forces and torques. Returned shape is (5, 12, 6) for the example: >>> # 5 envs, 9 DOFs (but 12 joints including the fixed and root joints) >>> prims.get_measured_joint_forces() [[[ 0.00000000e+00 0.00000000e+00 0.00000000e+00 0.00000000e+00 0.00000000e+00 0.00000000e+00] [ 1.49950760e+02 3.52353277e-06 5.62586996e-04 4.82502983e-05 -6.90729856e+00 2.69259126e-05] [-2.60467059e-05 -1.06778236e+02 -6.83844986e+01 -6.90730047e+00 -5.27759657e-05 -1.24897576e-06] [ 8.71209946e+01 -4.46646191e-05 -5.57951622e+01 5.33644052e-05 -2.45385647e+01 1.38957939e-05] [ 5.18576926e-05 -4.81099091e+01 6.07092705e+01 1.91570702e+01 -5.81023924e-05 1.46875891e-06] [-3.16910419e+01 2.31799815e-04 3.99901695e+01 -5.87591821e-05 -1.18634319e+00 2.24427877e-05] [-1.07621672e-04 1.53405371e+01 -1.54584875e+01 1.18634272e+00 6.09036942e-05 -1.60679410e-05] [-7.54189777e+00 -5.08146524e+00 -5.65130091e+00 -5.63882204e-05 3.88599992e-01 -3.49432468e-01] [ 4.74214745e+00 -3.19458222e+00 3.55281782e+00 5.58562024e-05 8.47946014e-03 7.64050474e-03] [ 4.07607269e+00 2.16406956e-01 -4.05131817e+00 -5.95658377e-04 1.14070829e-02 2.13965313e-06] [ 5.16803004e-03 -9.77545828e-02 -9.70939621e-02 -8.41282599e-12 -1.29066744e-12 -1.93477560e-11] [-5.19108167e-03 9.75882635e-02 -9.71064270e-02 8.41282859e-12 1.29066018e-12 -1.93477543e-11]] ... [[ 0.00000000e+00 0.00000000e+00 0.00000000e+00 0.00000000e+00 0.00000000e+00 0.00000000e+00] [ 1.49950760e+02 3.52353277e-06 5.62586996e-04 4.82502983e-05 -6.90729856e+00 2.69259126e-05] [-2.60467059e-05 -1.06778236e+02 -6.83844986e+01 -6.90730047e+00 -5.27759657e-05 -1.24897576e-06] [ 8.71209946e+01 -4.46646191e-05 -5.57951622e+01 5.33644052e-05 -2.45385647e+01 1.38957939e-05] [ 5.18576926e-05 -4.81099091e+01 6.07092705e+01 1.91570702e+01 -5.81023924e-05 1.46875891e-06] [-3.16910419e+01 2.31799815e-04 3.99901695e+01 -5.87591821e-05 -1.18634319e+00 2.24427877e-05] [-1.07621672e-04 1.53405371e+01 -1.54584875e+01 1.18634272e+00 6.09036942e-05 -1.60679410e-05] [-7.54189777e+00 -5.08146524e+00 -5.65130091e+00 -5.63882204e-05 3.88599992e-01 -3.49432468e-01] [ 4.74214745e+00 -3.19458222e+00 3.55281782e+00 5.58562024e-05 8.47946014e-03 7.64050474e-03] [ 4.07607269e+00 2.16406956e-01 -4.05131817e+00 -5.95658377e-04 1.14070829e-02 2.13965313e-06] [ 5.16803004e-03 -9.77545828e-02 -9.70939621e-02 -8.41282599e-12 -1.29066744e-12 -1.93477560e-11] [-5.19108167e-03 9.75882635e-02 -9.71064270e-02 8.41282859e-12 1.29066018e-12 -1.93477543e-11]]] >>> >>> # get measured joint forces and torques for the fingers for the first, middle and last of the 5 envs. >>> # Returned shape is (3, 2, 6) >>> metadata = prims._metadata >>> joint_indices = 1 + np.array([ >>> metadata.joint_indices["panda_finger_joint1"], >>> metadata.joint_indices["panda_finger_joint2"], >>> ]) >>> joint_indices [10 11] >>> prims.get_measured_joint_forces(indices=np.array([0, 2, 4]), joint_indices=joint_indices) [[[ 5.1680300e-03 -9.7754583e-02 -9.7093962e-02 -8.4128260e-12 -1.2906674e-12 -1.9347756e-11] [-5.1910817e-03 9.7588263e-02 -9.7106427e-02 8.4128286e-12 1.2906602e-12 -1.9347754e-11]] [[ 5.1680212e-03 -9.7754560e-02 -9.7093947e-02 -8.4141834e-12 -1.2907383e-12 -1.9348209e-11] [-5.1910840e-03 9.7588278e-02 -9.7106412e-02 8.4141869e-12 1.2907335e-12 -1.9348207e-11]] [[ 5.1680300e-03 -9.7754583e-02 -9.7093962e-02 -8.4128260e-12 -1.2906674e-12 -1.9347756e-11] [-5.1910817e-03 9.7588263e-02 -9.7106427e-02 8.4128286e-12 1.2906602e-12 -1.9347754e-11]]]
- get_sleep_thresholds(indices: Optional[Union[numpy.ndarray, List, torch.Tensor, warp.types.array]] = None) Union[numpy.ndarray, torch.Tensor, warp.types.indexedarray]
Get the threshold for articulations to enter a sleep state
Search for Articulations and Sleeping in PhysX docs for more details
- Parameters
indices (Optional[Union[np.ndarray, List, torch.Tensor, wp.array]], optional) – indices to specify which prims to query. Shape (M,). Where M <= size of the encapsulated prims in the view. Defaults to None (i.e: all prims in the view).
- Returns
sleep thresholds. shape (M,).
- Return type
Union[np.ndarray, torch.Tensor, wp.indexedarray]
Example:
>>> # get all sleep thresholds. Returned shape is (5,) for the example: 5 envs >>> prims.get_sleep_thresholds() [0.005 0.005 0.005 0.005 0.005] >>> >>> # get the sleep thresholds for the first, middle and last of the 5 envs. Returned shape is (3,) >>> prims.get_sleep_thresholds(indices=np.array([0, 2, 4])) [0.005 0.005 0.005]
- get_solver_position_iteration_counts(indices: Optional[Union[numpy.ndarray, List, torch.Tensor, warp.types.array]] = None) Union[numpy.ndarray, torch.Tensor, warp.types.indexedarray]
Get the solver (position) iteration count for the articulations
The solver iteration count determines how accurately contacts, drives, and limits are resolved. Search for Solver Iteration Count in PhysX docs for more details.
- Parameters
indices (Optional[Union[np.ndarray, List, torch.Tensor, wp.array]], optional) – indices to specify which prims to query. Shape (M,). Where M <= size of the encapsulated prims in the view. Defaults to None (i.e: all prims in the view).
- Returns
position iteration count. Shape (M,).
- Return type
Union[np.ndarray, torch.Tensor, wp.indexedarray]
Example:
>>> # get all position iteration count. Returned shape is (5,) for the example: 5 envs >>> prims.get_solver_position_iteration_counts() [32 32 32 32 32] >>> >>> # get the position iteration count for the first, middle and last of the 5 envs. Returned shape is (3,) >>> prims.get_solver_position_iteration_counts(indices=np.array([0, 2, 4])) [32 32 32]
- get_solver_velocity_iteration_counts(indices: Optional[Union[numpy.ndarray, List, torch.Tensor, warp.types.array]] = None) Union[numpy.ndarray, torch.Tensor, warp.types.indexedarray]
Get the solver (velocity) iteration count for the articulations
The solver iteration count determines how accurately contacts, drives, and limits are resolved. Search for Solver Iteration Count in PhysX docs for more details.
- Parameters
indices (Optional[Union[np.ndarray, List, torch.Tensor, wp.array]], optional) – indices to specify which prims to query. Shape (M,). Where M <= size of the encapsulated prims in the view. Defaults to None (i.e: all prims in the view).
- Returns
velocity iteration count. Shape (M,).
- Return type
Union[np.ndarray, torch.Tensor, wp.indexedarray]
Example:
>>> # get all velocity iteration count. Returned shape is (5,) for the example: 5 envs >>> prims.get_solver_velocity_iteration_counts() [32 32 32 32 32] >>> >>> # get the velocity iteration count for the first, middle and last of the 5 envs. Returned shape is (3,) >>> prims.get_solver_velocity_iteration_counts(indices=np.array([0, 2, 4])) [32 32 32]
- get_stabilization_thresholds(indices: Optional[Union[numpy.ndarray, List, torch.Tensor, warp.types.array]] = None) Union[numpy.ndarray, torch.Tensor, warp.types.indexedarray]
Get the mass-normalized kinetic energy below which the articulations may participate in stabilization
Search for Stabilization Threshold in PhysX docs for more details
- Parameters
indices (Optional[Union[np.ndarray, List, torch.Tensor, wp.array]], optional) – indices to specify which prims to query. Shape (M,). Where M <= size of the encapsulated prims in the view. Defaults to None (i.e: all prims in the view).
- Returns
stabilization threshold. Shape (M,).
- Return type
Union[np.ndarray, torch.Tensor, wp.indexedarray]
Example:
>>> # get all stabilization thresholds. Returned shape is (5,) for the example: 5 envs >>> prims.get_solver_velocity_iteration_counts() [0.001 0.001 0.001 0.001 0.001] >>> >>> # get the stabilization thresholds for the first, middle and last of the 5 envs. Returned shape is (3,) >>> prims.get_solver_velocity_iteration_counts(indices=np.array([0, 2, 4])) [0.001 0.001 0.001]
- get_velocities(indices: Optional[Union[numpy.ndarray, list, torch.Tensor, warp.types.array]] = None, clone: bool = True) Union[numpy.ndarray, torch.Tensor, warp.types.indexedarray]
Get the linear and angular velocities of prims in the view.
- Parameters
indices (Optional[Union[np.ndarray, list, torch.Tensor, wp.array]], optional) – indices to specify which prims to query. Shape (M,). Where M <= size of the encapsulated prims in the view. Defaults to None (i.e: all prims in the view)
clone (bool, optional) – True to return a clone of the internal buffer. Otherwise False. Defaults to True.
- Returns
linear and angular velocities of the prims in the view concatenated. shape is (M, 6). For the last dimension the first 3 values are for linear velocities and the last 3 for angular velocities
- Return type
Union[np.ndarray, torch.Tensor, wp.indexedarray]
Example:
>>> # get all articulation velocities. Returned shape is (5, 6) for the example: 5 envs, linear (3) and angular (3) >>> prims.get_velocities() [[0. 0. 0. 0. 0. 0.] [0. 0. 0. 0. 0. 0.] [0. 0. 0. 0. 0. 0.] [0. 0. 0. 0. 0. 0.] [0. 0. 0. 0. 0. 0.]] >>> >>> # get only the articulation velocities for the first, middle and last of the 5 envs. >>> # Returned shape is (3, 6) for the example: 3 envs selected, linear (3) and angular (3) >>> prims.get_velocities(indices=np.array([0, 2, 4])) [[0. 0. 0. 0. 0. 0.] [0. 0. 0. 0. 0. 0.] [0. 0. 0. 0. 0. 0.]]
- get_visibilities(indices: Optional[Union[numpy.ndarray, list, torch.Tensor, warp.types.array]] = None) Union[numpy.ndarray, torch.Tensor, warp.types.indexedarray]
Returns the current visibilities of the prims in stage.
- Parameters
indices (Optional[Union[np.ndarray, list, torch.Tensor, wp.array]], optional) – indices to specify which prims to query. Shape (M,). Where M <= size of the encapsulated prims in the view. Defaults to None (i.e: all prims in the view).
- Returns
- Shape (M,) with type bool, where each item holds True
if the prim is visible in stage. False otherwise.
- Return type
Union[np.ndarray, torch.Tensor, wp.indexedarray]
Example:
>>> # get all visibilities. Returned shape is (5,) for the example: 5 envs >>> prims.get_visibilities() [ True True True True True] >>> >>> # get the visibilities for the first, middle and last of the 5 envs. Returned shape is (3,) >>> prims.get_visibilities(indices=np.array([0, 2, 4])) [ True True True]
- get_world_poses(indices: Optional[Union[numpy.ndarray, list, torch.Tensor, warp.types.array]] = None, clone: bool = True, usd: bool = True) Union[Tuple[numpy.ndarray, numpy.ndarray], Tuple[torch.Tensor, torch.Tensor], Tuple[warp.types.indexedarray, warp.types.indexedarray]]
Get the poses of the prims in the view with respect to the world’s frame.
- Parameters
indices (Optional[Union[np.ndarray, list, torch.Tensor, wp.array]], optional) – indices to specify which prims to query. Shape (M,). Where M <= size of the encapsulated prims in the view. Defaults to None (i.e: all prims in the view).
clone (bool, optional) – True to return a clone of the internal buffer. Otherwise False. Defaults to True.
usd (bool, optional) – True to query from usd. Otherwise False to query from Fabric data. Defaults to True.
- Returns
first index is positions in the world frame of the prims. shape is (M, 3). Second index is quaternion orientations in the world frame of the prims. Quaternion is scalar-first (w, x, y, z). shape is (M, 4).
- Return type
Union[Tuple[np.ndarray, np.ndarray], Tuple[torch.Tensor, torch.Tensor], Tuple[wp.indexedarray, wp.indexedarray]]
Example:
>>> # get all articulation poses with respect to the world's frame. >>> # Returned shape is position (5, 3) and orientation (5, 4) for the example: 5 envs >>> positions, orientations = prims.get_world_poses() >>> positions [[ 1.5000000e+00 -7.5000000e-01 -2.8610229e-08] [ 1.5000000e+00 7.5000000e-01 -2.8610229e-08] [-4.5299529e-08 -7.5000000e-01 -2.8610229e-08] [-4.5299529e-08 7.5000000e-01 -2.8610229e-08] [-1.5000000e+00 -7.5000000e-01 -2.8610229e-08]] >>> orientations [[1. 0. 0. 0.] [1. 0. 0. 0.] [1. 0. 0. 0.] [1. 0. 0. 0.] [1. 0. 0. 0.]] >>> >>> # get only the articulation poses with respect to the world's frame for the first, middle and last of the 5 envs. >>> # Returned shape is position (3, 3) and orientation (3, 4) for the example: 3 envs selected >>> positions, orientations = prims.get_world_poses(indices=np.array([0, 2, 4])) >>> positions [[ 1.5000000e+00 -7.5000000e-01 -2.8610229e-08] [-4.5299529e-08 -7.5000000e-01 -2.8610229e-08] [-1.5000000e+00 -7.5000000e-01 -2.8610229e-08]] >>> orientations [[1. 0. 0. 0.] [1. 0. 0. 0.] [1. 0. 0. 0.]]
- get_world_scales(indices: Optional[Union[numpy.ndarray, list, torch.Tensor, warp.types.array]] = None) Union[numpy.ndarray, torch.Tensor, warp.types.indexedarray]
Get prim scales in the view with respect to the world’s frame
- Parameters
indices (Optional[Union[np.ndarray, list, torch.Tensor, wp.array]], optional) – indices to specify which prims to query. Shape (M,). Where M <= size of the encapsulated prims in the view. Defaults to None (i.e: all prims in the view).
- Returns
scales applied to the prim’s dimensions in the world frame. shape is (M, 3).
- Return type
Union[np.ndarray, torch.Tensor, wp.indexedarray]
Example:
>>> # get all prims scales with respect to the world's frame. >>> # Returned shape is (5, 3) for the example: 5 envs >>> prims.get_world_scales() [[1. 1. 1.] [1. 1. 1.] [1. 1. 1.] [1. 1. 1.] [1. 1. 1.]] >>> >>> # get only the prims scales with respect to the world's frame for the first, middle and last of the 5 envs. >>> # Returned shape is (3, 3) for the example: 3 envs selected >>> prims.get_world_scales(indices=np.array([0, 2, 4])) [[1. 1. 1.] [1. 1. 1.] [1. 1. 1.]]
- initialize(physics_sim_view: Optional[omni.physics.tensors.bindings._physicsTensors.SimulationView] = None) None
Create a physics simulation view if not passed and set other properties using the PhysX tensor API
Note
If the articulation view has been added to the world scene (e.g.,
world.scene.add(prims)), it will be automatically initialized when the world is reset (e.g.,world.reset()).Warning
This method needs to be called after each hard reset (e.g., Stop + Play on the timeline) before interacting with any other class method.
- Parameters
physics_sim_view (omni.physics.tensors.SimulationView, optional) – current physics simulation view. Defaults to None.
Example:
>>> prims.initialize()
- property initialized: bool
Check if articulation view is initialized
- Returns
True if the view object was initialized (after the first call of .initialize()). False otherwise.
- Return type
bool
Example:
>>> # given an initialized articulation view >>> prims.initialized True
- property is_non_root_articulation_link: bool
Returns: bool: True if the prim corresponds to a non root link in an articulation. Otherwise False.
- is_physics_handle_valid() bool
Check if articulation view’s physics handler is initialized
Warning
If the physics handler is not valid many of the methods that requires PhysX will return None.
- Returns
False if .initialize() needs to be called again for the physics handle to be valid. Otherwise True
- Return type
bool
Example:
>>> prims.is_physics_handle_valid() True
- is_valid(indices: Optional[Union[numpy.ndarray, list, torch.Tensor, warp.types.array]] = None) bool
Check that all prims have a valid USD Prim
- Parameters
indices (Optional[Union[np.ndarray, list, torch.Tensor, wp.array]], optional) – indices to specify which prims to query. Shape (M,). Where M <= size of the encapsulated prims in the view. Defaults to None (i.e: all prims in the view).
- Returns
True if all prim paths specified in the view correspond to a valid prim in stage. False otherwise.
- Return type
bool
Example:
>>> prims.is_valid() True
- is_visual_material_applied(indices: Optional[Union[numpy.ndarray, list, torch.Tensor, warp.types.array]] = None) List[bool]
Check if there is a visual material applied
- Parameters
indices (Optional[Union[np.ndarray, list, torch.Tensor, wp.array]], optional) – indices to specify which prims to query. Shape (M,). Where M <= size of the encapsulated prims in the view. Defaults to None (i.e: all prims in the view).
- Returns
True if there is a visual material applied is applied to the corresponding prim in the view. False otherwise.
- Return type
List[bool]
Example:
>>> # given a visual material that is applied only to the first and the last environment >>> prims.is_visual_material_applied() [True, False, False, False, True] >>> >>> # check for the first, middle and last of the 5 envs >>> prims.is_visual_material_applied(indices=np.array([0, 2, 4])) [True, False, True]
- property joint_names: List[str]
List of prim names for each joint of the articulations
- Returns
ordered names of joints that corresponds to degrees of freedom for the articulations in the view
- Return type
List[str]
- property name: str
Returns: str: name given to the prims view when instantiating it.
- property num_bodies: int
Number of rigid bodies (links) of the articulations
- Returns
maximum number of rigid bodies for the articulations in the view
- Return type
int
Example:
>>> prims.num_bodies 12
- property num_dof: int
Number of DOF of the articulations
- Returns
maximum number of DOFs for the articulations in the view
- Return type
int
Example:
>>> prims.num_dof 9
- property num_fixed_tendons: int
Number of fixed tendons of the articulations
- Returns
maximum number of fixed tendons for the articulations in the view
- Return type
int
Example:
>>> prims.num_fixed_tendons 0
- property num_joints: int
Number of joints of the articulations
- Returns
number of joints of the articulations in the view
- Return type
int
- property num_shapes: int
Number of rigid shapes of the articulations
- Returns
maximum number of rigid shapes for the articulations in the view
- Return type
int
Example:
>>> prims.num_shapes 17
- pause_motion() None
Pauses the motion of all articulations wrapped under the ArticulationView.
- post_reset() None
Reset the articulations to their default states
Note
For the articulations, in addition to configuring the root prim’s default positions and spatial orientations (defined via the
set_default_statemethod), the joint’s positions, velocities, and efforts (defined via theset_joints_default_statemethod) and the joint stiffnesses and dampings (defined via theset_gainsmethod) are imposedExample:
>>> prims.post_reset()
- property prim_paths: List[str]
- Returns
list of prim paths in the stage encapsulated in this view.
- Return type
List[str]
Example:
>>> prims.prim_paths ['/World/envs/env_0', '/World/envs/env_1', '/World/envs/env_2', '/World/envs/env_3', '/World/envs/env_4']
- property prims: List[pxr.Usd.Prim]
- Returns
List of USD Prim objects encapsulated in this view.
- Return type
List[Usd.Prim]
Example:
>>> prims.prims [Usd.Prim(</World/envs/env_0>), Usd.Prim(</World/envs/env_1>), Usd.Prim(</World/envs/env_2>), Usd.Prim(</World/envs/env_3>), Usd.Prim(</World/envs/env_4>)]
- resume_motion()
Resumes the motion of all articulations wrapped under the ArticulationView using the position and velocity dof targets cached when pause_motion was called.
- set_angular_velocities(velocities: Optional[Union[numpy.ndarray, torch.Tensor, warp.types.array]] = None, indices: Optional[Union[numpy.ndarray, list, torch.Tensor, warp.types.array]] = None) None
Set the angular velocities of the prims in the view
The method does this through the physx API only. It has to be called after initialization. Note: This method is not supported for the gpu pipeline.
set_velocitiesmethod should be used instead.Warning
This method will immediately set the articulation state
- Parameters
velocities (Optional[Union[np.ndarray, torch.Tensor, wp.array]]) – angular velocities to set the rigid prims to. shape is (M, 3).
indices (Optional[Union[np.ndarray, list, torch.Tensor, wp.array]], optional) – indices to specify which prims to manipulate. Shape (M,). Where M <= size of the encapsulated prims in the view. Defaults to None (i.e: all prims in the view).
Hint
This method belongs to the methods used to set the articulation kinematic state:
set_velocities(set_linear_velocities,set_angular_velocities),set_joint_positions,set_joint_velocities,set_joint_effortsExample:
>>> # set each articulation linear velocity to (0.1, 0.1, 0.1) >>> velocities = np.full((num_envs, 3), fill_value=0.1) >>> prims.set_angular_velocities(velocities) >>> >>> # set only the articulation linear velocities for the first, middle and last of the 5 envs >>> velocities = np.full((3, 3), fill_value=0.1) >>> prims.set_angular_velocities(velocities, indices=np.array([0, 2, 4]))
- set_armatures(values: Union[numpy.ndarray, torch.Tensor, warp.types.array], indices: Optional[Union[numpy.ndarray, List, torch.Tensor, warp.types.array]] = None, joint_indices: Optional[Union[numpy.ndarray, List, torch.Tensor, warp.types.array]] = None) None
Set armatures for articulation joints in the view
Search for “Joint Armature” in PhysX docs for more details.
- Parameters
values (Union[np.ndarray, torch.Tensor, wp.array]) – armatures for articulation joints in the view. shape (M, K).
indices (Optional[Union[np.ndarray, List, torch.Tensor, wp.array]], optional) – indices to specify which prims to manipulate. Shape (M,). Where M <= size of the encapsulated prims in the view. Defaults to None (i.e: all prims in the view).
joint_indices (Optional[Union[np.ndarray, List, torch.Tensor, wp.array]], optional) – joint indices to specify which joints to manipulate. Shape (K,). Where K <= num of dofs. Defaults to None (i.e: all dofs).
Example:
>>> # set all joint armatures to 0.05 for all envs >>> prims.set_armatures(np.full((num_envs, prims.num_dof), 0.05)) >>> >>> # set only the finger joint (panda_finger_joint1 (7) and panda_finger_joint2 (8)) armatures >>> # for the first, middle and last of the 5 envs to 0.05 >>> prims.set_armatures(np.full((3, 2), 0.05), indices=np.array([0,2,4]), joint_indices=np.array([7,8]))
- set_body_coms(positions: Optional[Union[numpy.ndarray, torch.Tensor, warp.types.array]] = None, orientations: Optional[Union[numpy.ndarray, torch.Tensor, warp.types.array]] = None, indices: Optional[Union[numpy.ndarray, List, torch.Tensor, warp.types.array]] = None, body_indices: Optional[Union[numpy.ndarray, List, torch.Tensor, warp.types.array]] = None) None
Set body center of mass (COM) positions and orientations for articulation bodies in the view.
- Parameters
positions (Union[np.ndarray, torch.Tensor, wp.array]) – body center of mass positions for articulations in the view. shape (M, K, 3).
orientations (Union[np.ndarray, torch.Tensor, wp.array]) – body center of mass orientations for articulations in the view. shape (M, K, 4).
indices (Optional[Union[np.ndarray, List, torch.Tensor, wp.array]], optional) – indices to specify which prims to manipulate. Shape (M,). Where M <= size of the encapsulated prims in the view. Defaults to None (i.e: all prims in the view).
body_indices (Optional[Union[np.ndarray, List, torch.Tensor, wp.array]], optional) – body indices to specify which bodies to manipulate. Shape (K,). Where K <= num of bodies. Defaults to None (i.e: all bodies).
Example:
>>> # set the center of mass for all the articulation rigid bodies to the indicated values. >>> # Since there are 5 envs, the inertias are repeated 5 times >>> positions = np.tile(np.array([0.01, 0.02, 0.03]), (num_envs, prims.num_bodies, 1)) >>> orientations = np.tile(np.array([1.0, 0.0, 0.0, 0.0]), (num_envs, prims.num_bodies, 1)) >>> prims.set_body_coms(positions, orientations) >>> >>> # set the fingers center of mass: panda_leftfinger (10) and panda_rightfinger (11) to 0.2 >>> # for the first, middle and last of the 5 envs >>> positions = np.tile(np.array([0.01, 0.02, 0.03]), (3, 2, 1)) >>> orientations = np.tile(np.array([1.0, 0.0, 0.0, 0.0]), (3, 2, 1)) >>> prims.set_body_coms(positions, orientations, indices=np.array([0, 2, 4]), body_indices=np.array([10, 11]))
- set_body_disable_gravity(values: Union[numpy.ndarray, torch.Tensor, warp.types.array], indices: Optional[Union[numpy.ndarray, List, torch.Tensor, warp.types.array]] = None, body_indices: Optional[Union[numpy.ndarray, List, torch.Tensor, warp.types.array]] = None) None
Set body gravity activation articulation bodies in the view.
- Parameters
values (Union[np.ndarray, torch.Tensor, wp.array]) – body gravity activation for articulations in the view. shape (M, K).
indices (Optional[Union[np.ndarray, List, torch.Tensor, wp.array]], optional) – indices to specify which prims to manipulate. Shape (M,). Where M <= size of the encapsulated prims in the view. Defaults to None (i.e: all prims in the view).
body_indices (Optional[Union[np.ndarray, List, torch.Tensor, wp.array]], optional) – body indices to specify which bodies to manipulate. Shape (K,). Where K <= num of bodies. Defaults to None (i.e: all bodies).
- set_body_inertias(values: Union[numpy.ndarray, torch.Tensor, warp.types.array], indices: Optional[Union[numpy.ndarray, List, torch.Tensor, warp.types.array]] = None, body_indices: Optional[Union[numpy.ndarray, List, torch.Tensor, warp.types.array]] = None) None
Set body inertias for articulation bodies in the view.
- Parameters
values (Union[np.ndarray, torch.Tensor, wp.array]) – body inertias for articulations in the view. shape (M, K, 9).
indices (Optional[Union[np.ndarray, List, torch.Tensor, wp.array]], optional) – indices to specify which prims to manipulate. Shape (M,). Where M <= size of the encapsulated prims in the view. Defaults to None (i.e: all prims in the view).
body_indices (Optional[Union[np.ndarray, List, torch.Tensor, wp.array]], optional) – body indices to specify which bodies to manipulate. Shape (K,). Where K <= num of bodies. Defaults to None (i.e: all bodies).
Example:
>>> # set the inertias for all the articulation rigid bodies to the indicated values. >>> # Since there are 5 envs, the inertias are repeated 5 times >>> inertias = np.tile(np.array([0.1, 0.0, 0.0, 0.0, 0.1, 0.0, 0.0, 0.0, 0.1]), (num_envs, prims.num_bodies, 1)) >>> prims.set_body_inertias(inertias) >>> >>> # set the fingers inertias: panda_leftfinger (10) and panda_rightfinger (11) to 0.2 >>> # for the first, middle and last of the 5 envs >>> inertias = np.tile(np.array([0.1, 0.0, 0.0, 0.0, 0.1, 0.0, 0.0, 0.0, 0.1]), (3, 2, 1)) >>> prims.set_body_inertias(inertias, indices=np.array([0, 2, 4]), body_indices=np.array([10, 11]))
- set_body_masses(values: Union[numpy.ndarray, torch.Tensor, warp.types.array], indices: Optional[Union[numpy.ndarray, List, torch.Tensor, warp.types.array]] = None, body_indices: Optional[Union[numpy.ndarray, List, torch.Tensor, warp.types.array]] = None) None
Set body masses for articulation bodies in the view
- Parameters
values (Union[np.ndarray, torch.Tensor, wp.array]) – body masses for articulations in the view. shape (M, K).
indices (Optional[Union[np.ndarray, List, torch.Tensor, wp.array]], optional) – indices to specify which prims to manipulate. Shape (M,). Where M <= size of the encapsulated prims in the view. Defaults to None (i.e: all prims in the view).
body_indices (Optional[Union[np.ndarray, List, torch.Tensor, wp.array]], optional) – body indices to specify which bodies to manipulate. Shape (K,). Where K <= num of bodies. Defaults to None (i.e: all bodies).
Example:
>>> # set the masses for all the articulation rigid bodies to the indicated values. >>> # Since there are 5 envs, the masses are repeated 5 times >>> masses = np.tile(np.array([1.2, 1.1, 1.0, 0.9, 0.8, 0.7, 0.6, 0.5, 0.4, 0.3, 0.2, 0.2]), (num_envs, 1)) >>> prims.set_body_masses(masses) >>> >>> # set the fingers masses: panda_leftfinger (10) and panda_rightfinger (11) to 0.2 >>> # for the first, middle and last of the 5 envs >>> masses = np.tile(np.array([0.2, 0.2]), (3, 1)) >>> prims.set_body_masses(masses, indices=np.array([0, 2, 4]), body_indices=np.array([10, 11]))
- set_default_state(positions: Optional[Union[numpy.ndarray, torch.Tensor, warp.types.array]] = None, orientations: Optional[Union[numpy.ndarray, torch.Tensor, warp.types.array]] = None, indices: Optional[Union[numpy.ndarray, list, torch.Tensor, warp.types.array]] = None) None
Set the default state of the prims (positions and orientations), that will be used after each reset.
Note
The default states will be set during post-reset (e.g., calling
.post_reset()orworld.reset()methods)- Parameters
positions (Optional[Union[np.ndarray, torch.Tensor, wp.array]], optional) – positions in the world frame of the prim. shape is (M, 3). Defaults to None, which means left unchanged.
orientations (Optional[Union[np.ndarray, torch.Tensor, wp.array]], optional) – quaternion orientations in the world frame of the prim. quaternion is scalar-first (w, x, y, z). shape is (M, 4). Defaults to None, which means left unchanged.
indices (Optional[Union[np.ndarray, list, torch.Tensor, wp.array]], optional) – indices to specify which prims to manipulate. Shape (M,). Where M <= size of the encapsulated prims in the view. Defaults to None (i.e: all prims in the view).
Example:
>>> # configure default states for all prims >>> positions = np.zeros((num_envs, 3)) >>> positions[:, 0] = np.arange(num_envs) >>> orientations = np.tile(np.array([1.0, 0.0, 0.0, 0.0]), (num_envs, 1)) >>> prims.set_default_state(positions=positions, orientations=orientations) >>> >>> # set default states during post-reset >>> prims.post_reset()
- set_effort_modes(mode: str, indices: Optional[Union[numpy.ndarray, List, torch.Tensor, warp.types.array]] = None, joint_indices: Optional[Union[numpy.ndarray, List, torch.Tensor]] = None) None
Set effort modes for articulations in the view
- Parameters
mode (str) – effort mode to be applied to prims in the view:
accelerationorforce.indices (Optional[Union[np.ndarray, List, torch.Tensor, wp.array]], optional) – indices to specify which prims to manipulate. Shape (M,). Where M <= size of the encapsulated prims in the view. Defaults to None (i.e: all prims in the view).
joint_indices (Optional[Union[np.ndarray, List, torch.Tensor, wp.array]], optional) – joint indices to specify which joints to manipulate. Shape (K,). Where K <= num of dofs. Defaults to None (i.e: all dofs).
Example:
>>> # set the effort mode for all joints to 'force' >>> prims.set_effort_modes("force") >>> >>> # set only the finger joints effort mode to 'force' for the first, middle and last of the 5 envs >>> prims.set_effort_modes("force", indices=np.array([0, 2, 4]), joint_indices=np.array([7, 8]))
- set_enabled_self_collisions(flags: Union[numpy.ndarray, torch.Tensor, warp.types.array], indices: Optional[Union[numpy.ndarray, List, torch.Tensor, warp.types.array]] = None) None
Set the enable self collisions flag (
physxArticulation:enabledSelfCollisions)- Parameters
flags (Union[np.ndarray, torch.Tensor, wp.array]) – true to enable self collision. otherwise false. shape (M,)
indices (Optional[Union[np.ndarray, List, torch.Tensor, wp.array]], optional) – indices to specify which prims to manipulate. Shape (M,). Where M <= size of the encapsulated prims in the view. Defaults to None (i.e: all prims in the view).
Example:
>>> # enable the self collisions flag for all envs >>> prims.set_enabled_self_collisions(np.full((num_envs,), True)) >>> >>> # enable the self collisions flag only for the first, middle and last of the 5 envs >>> prims.set_enabled_self_collisions(np.full((3,), True), indices=np.array([0, 2, 4]))
- set_fixed_tendon_properties(stiffnesses: Optional[Union[numpy.ndarray, torch.Tensor, warp.types.array]] = None, dampings: Optional[Union[numpy.ndarray, torch.Tensor, warp.types.array]] = None, limit_stiffnesses: Optional[Union[numpy.ndarray, torch.Tensor, warp.types.array]] = None, limits: Optional[Union[numpy.ndarray, torch.Tensor, warp.types.array]] = None, rest_lengths: Optional[Union[numpy.ndarray, torch.Tensor, warp.types.array]] = None, offsets: Optional[Union[numpy.ndarray, torch.Tensor, warp.types.array]] = None, indices: Optional[Union[numpy.ndarray, List, torch.Tensor, warp.types.array]] = None) None
Set fixed tendon properties for articulations in the view
Search for Fixed Tendon in PhysX docs for more details
- Parameters
stiffnesses (Union[np.ndarray, torch.Tensor, wp.array]) – fixed tendon stiffnesses for articulations in the view. shape (M, K).
dampings (Union[np.ndarray, torch.Tensor, wp.array]) – fixed tendon dampings for articulations in the view. shape (M, K).
limit_stiffnesses (Union[np.ndarray, torch.Tensor, wp.array]) – fixed tendon limit stiffnesses for articulations in the view. shape (M, K).
limits (Union[np.ndarray, torch.Tensor, wp.array]) – fixed tendon limits for articulations in the view. shape (M, K, 2).
rest_lengths (Union[np.ndarray, torch.Tensor, wp.array]) – fixed tendon rest lengths for articulations in the view. shape (M, K).
offsets (Union[np.ndarray, torch.Tensor, wp.array]) – fixed tendon offsets for articulations in the view. shape (M, K).
indices (Optional[Union[np.ndarray, List, torch.Tensor, wp.array]], optional) – indices to specify which prims to manipulate. Shape (M,). Where M <= size of the encapsulated prims in the view. Defaults to None (i.e: all prims in the view).
Example:
>>> # set the limit stiffnesses and dampings >>> # for the ShadowHand articulation that has 4 fixed tendons (prims.num_fixed_tendons) >>> limit_stiffnesses = np.full((num_envs, prims.num_fixed_tendons), fill_value=10.0) >>> dampings = np.full((num_envs, prims.num_fixed_tendons), fill_value=0.1) >>> prims.set_fixed_tendon_properties(dampings=dampings, limit_stiffnesses=limit_stiffnesses)
- set_friction_coefficients(values: Union[numpy.ndarray, torch.Tensor], indices: Optional[Union[numpy.ndarray, List, torch.Tensor, warp.types.array]] = None, joint_indices: Optional[Union[numpy.ndarray, List, torch.Tensor, warp.types.array]] = None) None
Set the friction coefficients for articulation joints in the view
Search for “Joint Friction Coefficient” in PhysX docs for more details.
- Parameters
values (Union[np.ndarray, torch.Tensor, wp.array]) – friction coefficients for articulation joints in the view. shape (M, K).
indices (Optional[Union[np.ndarray, List, torch.Tensor, wp.array]], optional) – indices to specify which prims to manipulate. Shape (M,). Where M <= size of the encapsulated prims in the view. Defaults to None (i.e: all prims in the view).
joint_indices (Optional[Union[np.ndarray, List, torch.Tensor, wp.array]], optional) – joint indices to specify which joints to manipulate. Shape (K,). Where K <= num of dofs. Defaults to None (i.e: all dofs).
Example:
>>> # set all joint friction coefficients to 0.05 for all envs >>> prims.set_friction_coefficients(np.full((num_envs, prims.num_dof), 0.05)) >>> >>> # set only the finger joint (panda_finger_joint1 (7) and panda_finger_joint2 (8)) friction coefficients >>> # for the first, middle and last of the 5 envs to 0.05 >>> prims.set_friction_coefficients(np.full((3, 2), 0.05), indices=np.array([0,2,4]), joint_indices=np.array([7,8]))
- set_gains(kps: Optional[Union[numpy.ndarray, torch.Tensor, warp.types.array]] = None, kds: Optional[Union[numpy.ndarray, torch.Tensor, warp.types.array]] = None, indices: Optional[Union[numpy.ndarray, List, torch.Tensor, warp.types.array]] = None, joint_indices: Optional[Union[numpy.ndarray, List, torch.Tensor, warp.types.array]] = None, save_to_usd: bool = False) None
Set the implicit Proportional-Derivative (PD) controller’s Kps (stiffnesses) and Kds (dampings) of articulations in the view
- Parameters
kps (Optional[Union[np.ndarray, torch.Tensor, wp.array]], optional) – stiffness of the drives. shape is (M, K). Defaults to None.
kds (Optional[Union[np.ndarray, torch.Tensor, wp.array]], optional) – damping of the drives. shape is (M, K).. Defaults to None.
indices (Optional[Union[np.ndarray, List, torch.Tensor, wp.array]], optional) – indices to specify which prims to manipulate. Shape (M,). Where M <= size of the encapsulated prims in the view. Defaults to None (i.e: all prims in the view).
joint_indices (Optional[Union[np.ndarray, List, torch.Tensor, wp.array]], optional) – joint indices to specify which joints to manipulate. Shape (K,). Where K <= num of dofs. Defaults to None (i.e: all dofs).
save_to_usd (bool, optional) – True to save the gains in the usd. otherwise False.
Example:
>>> # set the gains (stiffnesses and dampings) for all the articulation joints to the indicated values. >>> # Since there are 5 envs, the gains are repeated 5 times >>> stiffnesses = np.tile(np.array([100000, 100000, 100000, 100000, 80000, 80000, 80000, 50000, 50000]), (num_envs, 1)) >>> dampings = np.tile(np.array([8000, 8000, 8000, 8000, 5000, 5000, 5000, 2000, 2000]), (num_envs, 1)) >>> prims.set_gains(kps=stiffnesses, kds=dampings) >>> >>> # set the fingers gains (stiffnesses and dampings): panda_finger_joint1 (7) and panda_finger_joint2 (8) >>> # to 50000 and 2000 respectively for the first, middle and last of the 5 envs >>> stiffnesses = np.tile(np.array([50000, 50000]), (3, 1)) >>> dampings = np.tile(np.array([2000, 2000]), (3, 1)) >>> prims.set_gains(kps=stiffnesses, kds=dampings, indices=np.array([0, 2, 4]), joint_indices=np.array([7, 8]))
- set_joint_efforts(efforts: Optional[Union[numpy.ndarray, torch.Tensor, warp.types.array]], indices: Optional[Union[numpy.ndarray, List, torch.Tensor, warp.types.array]] = None, joint_indices: Optional[Union[numpy.ndarray, List, torch.Tensor, warp.types.array]] = None) None
Set the joint efforts of articulations in the view
Note
This method can be used for effort control. For this purpose, there must be no joint drive or the stiffness and damping must be set to zero.
- Parameters
efforts (Optional[Union[np.ndarray, torch.Tensor, wp.array]]) – efforts of articulations in the view to be set to in the next frame. shape is (M, K).
indices (Optional[Union[np.ndarray, List, torch.Tensor, wp.array]], optional) – indices to specify which prims to manipulate. Shape (M,). Where M <= size of the encapsulated prims in the view. Defaults to None (i.e: all prims in the view).
joint_indices (Optional[Union[np.ndarray, List, torch.Tensor, wp.array]], optional) – joint indices to specify which joints to manipulate. Shape (K,). Where K <= num of dofs. Defaults to None (i.e: all dofs).
Hint
This method belongs to the methods used to set the articulation kinematic states:
set_velocities(set_linear_velocities,set_angular_velocities),set_joint_positions,set_joint_velocities,set_joint_effortsExample:
>>> # set the efforts for all the articulation joints to the indicated values. >>> # Since there are 5 envs, the joint efforts are repeated 5 times >>> efforts = np.tile(np.array([10, 20, 30, 40, 50, 60, 70, 80, 90]), (num_envs, 1)) >>> prims.set_joint_efforts(efforts) >>> >>> # set the fingers efforts: panda_finger_joint1 (7) and panda_finger_joint2 (8) to 10 >>> # for the first, middle and last of the 5 envs >>> efforts = np.tile(np.array([10, 10]), (3, 1)) >>> prims.set_joint_efforts(efforts, indices=np.array([0, 2, 4]), joint_indices=np.array([7, 8]))
- set_joint_position_targets(positions: Optional[Union[numpy.ndarray, torch.Tensor, warp.types.array]], indices: Optional[Union[numpy.ndarray, List, torch.Tensor, warp.types.array]] = None, joint_indices: Optional[Union[numpy.ndarray, List, torch.Tensor, warp.types.array]] = None) None
Set the joint position targets for the implicit Proportional-Derivative (PD) controllers
Note
This is an independent method for controlling joints. To apply multiple targets (position, velocity, and/or effort) in the same call, consider using the
apply_actionmethod- Parameters
positions (Optional[Union[np.ndarray, torch.Tensor, wp.array]]) – joint position targets for the implicit PD controller. shape is (M, K).
indices (Optional[Union[np.ndarray, List, torch.Tensor, wp.array]], optional) – indices to specify which prims to manipulate. Shape (M,). Where M <= size of the encapsulated prims in the view. Defaults to None (i.e: all prims in the view).
joint_indices (Optional[Union[np.ndarray, List, torch.Tensor, wp.array]], optional) – joint indices to specify which joints to manipulate. Shape (K,). Where K <= num of dofs. Defaults to None (i.e: all dofs).
Hint
High stiffness makes the joints snap faster and harder to the desired target, and higher damping smoothes but also slows down the joint’s movement to target
For position control, set relatively high stiffness and low damping (to reduce vibrations)
Example:
>>> # apply the target positions (to move all the robot joints) to the indicated values. >>> # Since there are 5 envs, the joint positions are repeated 5 times >>> positions = np.tile(np.array([0.0, -1.0, 0.0, -2.2, 0.0, 2.4, 0.8, 0.04, 0.04]), (num_envs, 1)) >>> prims.set_joint_position_targets(positions) >>> >>> # close the robot fingers: panda_finger_joint1 (7) and panda_finger_joint2 (8) to 0.0 >>> # for the first, middle and last of the 5 envs >>> positions = np.tile(np.array([0.0, 0.0]), (3, 1)) >>> prims.set_joint_position_targets(positions, indices=np.array([0, 2, 4]), joint_indices=np.array([7, 8]))
- set_joint_positions(positions: Optional[Union[numpy.ndarray, torch.Tensor, warp.types.array]], indices: Optional[Union[numpy.ndarray, List, torch.Tensor, warp.types.array]] = None, joint_indices: Optional[Union[numpy.ndarray, List, torch.Tensor, warp.types.array]] = None) None
Set the joint positions of articulations in the view
Warning
This method will immediately set (teleport) the affected joints to the indicated value. Use the
set_joint_position_targetsor theapply_actionmethods to control the articulation joints.- Parameters
positions (Optional[Union[np.ndarray, torch.Tensor, wp.array]]) – joint positions of articulations in the view to be set to in the next frame. shape is (M, K).
indices (Optional[Union[np.ndarray, List, torch.Tensor, wp.array]], optional) – indices to specify which prims to manipulate. Shape (M,). Where M <= size of the encapsulated prims in the view. Defaults to None (i.e: all prims in the view).
joint_indices (Optional[Union[np.ndarray, List, torch.Tensor, wp.array]], optional) – joint indices to specify which joints to manipulate. Shape (K,). Where K <= num of dofs. Defaults to None (i.e: all dofs).
Hint
This method belongs to the methods used to set the articulation kinematic states:
set_velocities(set_linear_velocities,set_angular_velocities),set_joint_positions,set_joint_velocities,set_joint_effortsExample:
>>> # set all the articulation joints. >>> # Since there are 5 envs, the joint positions are repeated 5 times >>> positions = np.tile(np.array([0.0, -1.0, 0.0, -2.2, 0.0, 2.4, 0.8, 0.04, 0.04]), (num_envs, 1)) >>> prims.set_joint_positions(positions) >>> >>> # set only the fingers in closed position: panda_finger_joint1 (7) and panda_finger_joint2 (8) to 0.0 >>> # for the first, middle and last of the 5 envs >>> positions = np.tile(np.array([0.0, 0.0]), (3, 1)) >>> prims.set_joint_positions(positions, indices=np.array([0, 2, 4]), joint_indices=np.array([7, 8]))
- set_joint_velocities(velocities: Optional[Union[numpy.ndarray, torch.Tensor, warp.types.array]], indices: Optional[Union[numpy.ndarray, List, torch.Tensor, warp.types.array]] = None, joint_indices: Optional[Union[numpy.ndarray, List, torch.Tensor, warp.types.array]] = None) None
Set the joint velocities of articulations in the view
Warning
This method will immediately set the affected joints to the indicated value. Use the
set_joint_velocity_targetsor theapply_actionmethods to control the articulation joints.- Parameters
velocities (Optional[Union[np.ndarray, torch.Tensor, wp.array]]) – joint velocities of articulations in the view to be set to in the next frame. shape is (M, K).
indices (Optional[Union[np.ndarray, List, torch.Tensor, wp.array]], optional) – indices to specify which prims to manipulate. Shape (M,). Where M <= size of the encapsulated prims in the view. Defaults to None (i.e: all prims in the view).
joint_indices (Optional[Union[np.ndarray, List, torch.Tensor, wp.array]], optional) – joint indices to specify which joints to manipulate. Shape (K,). Where K <= num of dofs. Defaults to None (i.e: all dofs).
Hint
This method belongs to the methods used to set the articulation kinematic states:
set_velocities(set_linear_velocities,set_angular_velocities),set_joint_positions,set_joint_velocities,set_joint_effortsExample:
>>> # set the velocities for all the articulation joints to the indicated values. >>> # Since there are 5 envs, the joint velocities are repeated 5 times >>> velocities = np.tile(np.array([0.1, 0.2, 0.3, 0.4, 0.5, 0.6, 0.7, 0.8, 0.9]), (num_envs, 1)) >>> prims.set_joint_velocities(velocities) >>> >>> # set the fingers velocities: panda_finger_joint1 (7) and panda_finger_joint2 (8) to -0.1 >>> # for the first, middle and last of the 5 envs >>> velocities = np.tile(np.array([-0.1, -0.1]), (3, 1)) >>> prims.set_joint_velocities(velocities, indices=np.array([0, 2, 4]), joint_indices=np.array([7, 8]))
- set_joint_velocity_targets(velocities: Optional[Union[numpy.ndarray, torch.Tensor, warp.types.array]], indices: Optional[Union[numpy.ndarray, List, torch.Tensor, warp.types.array]] = None, joint_indices: Optional[Union[numpy.ndarray, List, torch.Tensor, warp.types.array]] = None) None
Set the joint velocity targets for the implicit Proportional-Derivative (PD) controllers
Note
This is an independent method for controlling joints. To apply multiple targets (position, velocity, and/or effort) in the same call, consider using the
apply_actionmethod- Parameters
velocities (Optional[Union[np.ndarray, torch.Tensor, wp.array]]) – joint velocity targets for the implicit PD controller. shape is (M, K).
indices (Optional[Union[np.ndarray, List, torch.Tensor, wp.array]], optional) – indices to specify which prims to manipulate. Shape (M,). Where M <= size of the encapsulated prims in the view. Defaults to None (i.e: all prims in the view).
joint_indices (Optional[Union[np.ndarray, List, torch.Tensor, wp.array]], optional) – joint indices to specify which joints to manipulate. Shape (K,). Where K <= num of dofs. Defaults to None (i.e: all dofs).
Hint
High stiffness makes the joints snap faster and harder to the desired target, and higher damping smoothes but also slows down the joint’s movement to target
For velocity control, stiffness must be set to zero with a non-zero damping
Example:
>>> # apply the target velocities for all the articulation joints to the indicated values. >>> # Since there are 5 envs, the joint velocities are repeated 5 times >>> velocities = np.tile(np.array([0.1, 0.2, 0.3, 0.4, 0.5, 0.6, 0.7, 0.8, 0.9]), (num_envs, 1)) >>> prims.set_joint_velocity_targets(velocities) >>> >>> # apply the fingers target velocities: panda_finger_joint1 (7) and panda_finger_joint2 (8) to -1.0 >>> # for the first, middle and last of the 5 envs >>> velocities = np.tile(np.array([-0.1, -0.1]), (3, 1)) >>> prims.set_joint_velocity_targets(velocities, indices=np.array([0, 2, 4]), joint_indices=np.array([7, 8]))
- set_joints_default_state(positions: Optional[Union[numpy.ndarray, torch.Tensor, warp.types.array]] = None, velocities: Optional[Union[numpy.ndarray, torch.Tensor, warp.types.array]] = None, efforts: Optional[Union[numpy.ndarray, torch.Tensor, warp.types.array]] = None) None
Set the joints default state (joint positions, velocities and efforts) to be applied after each reset.
Note
The default states will be set during post-reset (e.g., calling
.post_reset()orworld.reset()methods)- Parameters
positions (Optional[Union[np.ndarray, torch.Tensor, wp.array]], optional) – default joint positions. shape is (N, num of dofs). Defaults to None.
velocities (Optional[Union[np.ndarray, torch.Tensor, wp.array]], optional) – default joint velocities. shape is (N, num of dofs). Defaults to None.
efforts (Optional[Union[np.ndarray, torch.Tensor, wp.array]], optional) – default joint efforts. shape is (N, num of dofs). Defaults to None.
Example:
>>> # configure default joint states for all articulations >>> positions = np.tile(np.array([0.0, -1.0, 0.0, -2.2, 0.0, 2.4, 0.8, 0.04, 0.04]), (num_envs, 1)) >>> prims.set_joints_default_state( ... positions=positions, ... velocities=np.zeros((num_envs, prims.num_dof)), ... efforts=np.zeros((num_envs, prims.num_dof)) ... ) >>> >>> # set default states during post-reset >>> prims.post_reset()
- set_linear_velocities(velocities: Optional[Union[numpy.ndarray, torch.Tensor, warp.types.array]] = None, indices: Optional[Union[numpy.ndarray, list, torch.Tensor, warp.types.array]] = None) None
Set the linear velocities of the prims in the view
The method does this through the PhysX API only. It has to be called after initialization. Note: This method is not supported for the gpu pipeline.
set_velocitiesmethod should be used instead.Warning
This method will immediately set the articulation state
- Parameters
velocities (Optional[Union[np.ndarray, torch.Tensor, wp.array]]) – linear velocities to set the rigid prims to. shape is (M, 3).
indices (Optional[Union[np.ndarray, list, torch.Tensor, wp.array]], optional) – indices to specify which prims to manipulate. Shape (M,). Where M <= size of the encapsulated prims in the view. Defaults to None (i.e: all prims in the view).
Hint
This method belongs to the methods used to set the articulation kinematic state:
set_velocities(set_linear_velocities,set_angular_velocities),set_joint_positions,set_joint_velocities,set_joint_effortsExample:
>>> # set each articulation linear velocity to (1.0, 1.0, 1.0) >>> velocities = np.ones((num_envs, 3)) >>> prims.set_linear_velocities(velocities) >>> >>> # set only the articulation linear velocities for the first, middle and last of the 5 envs >>> velocities = np.ones((3, 3)) >>> prims.set_linear_velocities(velocities, indices=np.array([0, 2, 4]))
- set_local_poses(translations: Optional[Union[numpy.ndarray, torch.Tensor, warp.types.array]] = None, orientations: Optional[Union[numpy.ndarray, torch.Tensor, warp.types.array]] = None, indices: Optional[Union[numpy.ndarray, list, torch.Tensor, warp.types.array]] = None) None
Set prim poses in the view with respect to the local frame (the prim’s parent frame).
Warning
This method will change (teleport) the prim poses immediately to the indicated value
- Parameters
translations (Optional[Union[np.ndarray, torch.Tensor, wp.array]], optional) – translations in the local frame of the prims (with respect to its parent prim). shape is (M, 3). Defaults to None, which means left unchanged.
orientations (Optional[Union[np.ndarray, torch.Tensor, wp.array]], optional) – quaternion orientations in the local frame of the prims. quaternion is scalar-first (w, x, y, z). shape is (M, 4). Defaults to None, which means left unchanged.
indices (Optional[Union[np.ndarray, list, torch.Tensor, wp.array]], optional) – indices to specify which prims to manipulate. Shape (M,). Where M <= size of the encapsulated prims in the view. Defaults to None (i.e: all prims in the view).
Hint
This method belongs to the methods used to set the prim state
Example:
>>> # reposition all articulations >>> positions = np.zeros((num_envs, 3)) >>> positions[:,0] = np.arange(num_envs) >>> orientations = np.tile(np.array([1.0, 0.0, 0.0, 0.0]), (num_envs, 1)) >>> prims.set_local_poses(positions, orientations) >>> >>> # reposition only the articulations for the first, middle and last of the 5 envs >>> positions = np.zeros((3, 3)) >>> positions[:,1] = np.arange(3) >>> orientations = np.tile(np.array([1.0, 0.0, 0.0, 0.0]), (3, 1)) >>> prims.set_local_poses(positions, orientations, indices=np.array([0, 2, 4]))
- set_local_scales(scales: Optional[Union[numpy.ndarray, torch.Tensor, warp.types.array]], indices: Optional[Union[numpy.ndarray, list, torch.Tensor, warp.types.array]] = None) None
Set prim scales in the view with respect to the local frame (the prim’s parent frame)
- Parameters
scales (Optional[Union[np.ndarray, torch.Tensor, wp.array]]) – scales to be applied to the prim’s dimensions in the view. shape is (M, 3).
indices (Optional[Union[np.ndarray, list, torch.Tensor, wp.array]], optional) – indices to specify which prims to manipulate. Shape (M,). Where M <= size of the encapsulated prims in the view. Defaults to None (i.e: all prims in the view).
Example:
>>> # set the scale for all prims. Since there are 5 envs, the scale is repeated 5 times >>> scales = np.tile(np.array([1.0, 0.75, 0.5]), (num_envs, 1)) >>> prims.set_local_scales(scales) >>> >>> # set the scale for the first, middle and last of the 5 envs >>> scales = np.tile(np.array([1.0, 0.75, 0.5]), (3, 1)) >>> prims.set_local_scales(scales, indices=np.array([0, 2, 4]))
- set_max_efforts(values: Union[numpy.ndarray, torch.Tensor, warp.types.array], indices: Optional[Union[numpy.ndarray, List, torch.Tensor, warp.types.array]] = None, joint_indices: Optional[Union[numpy.ndarray, List, torch.Tensor, warp.types.array]] = None) None
Set maximum efforts for articulation in the view
- Parameters
values (Union[np.ndarray, torch.Tensor, wp.array]) – maximum efforts for articulations in the view. shape (M, K).
indices (Optional[Union[np.ndarray, List, torch.Tensor, wp.array]], optional) – indices to specify which prims to manipulate. Shape (M,). Where M <= size of the encapsulated prims in the view. Defaults to None (i.e: all prims in the view).
joint_indices (Optional[Union[np.ndarray, List, torch.Tensor, wp.array]], optional) – joint indices to specify which joints to manipulate. Shape (K,). Where K <= num of dofs. Defaults to None (i.e: all dofs).
Example:
>>> # set the max efforts for all the articulation joints to the indicated values. >>> # Since there are 5 envs, the joint efforts are repeated 5 times >>> max_efforts = np.tile(np.array([10000, 9000, 8000, 7000, 6000, 5000, 4000, 1000, 1000]), (num_envs, 1)) >>> prims.set_max_efforts(max_efforts) >>> >>> # set the fingers max efforts: panda_finger_joint1 (7) and panda_finger_joint2 (8) to 1000 >>> # for the first, middle and last of the 5 envs >>> max_efforts = np.tile(np.array([1000, 1000]), (3, 1)) >>> prims.set_max_efforts(max_efforts, indices=np.array([0, 2, 4]), joint_indices=np.array([7, 8]))
- set_max_joint_velocities(values: Union[numpy.ndarray, torch.Tensor, warp.types.array], indices: Optional[Union[numpy.ndarray, List, torch.Tensor, warp.types.array]] = None, joint_indices: Optional[Union[numpy.ndarray, List, torch.Tensor, warp.types.array]] = None) None
Set maximum velocities for articulation in the view
- Parameters
values (Union[np.ndarray, torch.Tensor, wp.array]) – maximum velocities for articulations in the view. shape (M, K).
indices (Optional[Union[np.ndarray, List, torch.Tensor, wp.array]], optional) – indices to specify which prims to manipulate. Shape (M,). Where M <= size of the encapsulated prims in the view. Defaults to None (i.e: all prims in the view).
joint_indices (Optional[Union[np.ndarray, List, torch.Tensor, wp.array]], optional) – joint indices to specify which joints to manipulate. Shape (K,). Where K <= num of dofs. Defaults to None (i.e: all dofs).
- set_sleep_thresholds(thresholds: Union[numpy.ndarray, torch.Tensor, warp.types.array], indices: Optional[Union[numpy.ndarray, List, torch.Tensor, warp.types.array]] = None) None
Set the threshold for articulations to enter a sleep state
Search for Articulations and Sleeping in PhysX docs for more details
- Parameters
thresholds (Union[np.ndarray, torch.Tensor, wp.array]) – sleep thresholds to be applied. shape (M,).
indices (Optional[Union[np.ndarray, List, torch.Tensor, wp.array]], optional) – indices to specify which prims to manipulate. Shape (M,). Where M <= size of the encapsulated prims in the view. Defaults to None (i.e: all prims in the view).
Example:
>>> # set the sleep threshold for all envs >>> prims.set_sleep_thresholds(np.full((num_envs,), 0.01)) >>> >>> # set only the sleep threshold for the first, middle and last of the 5 envs >>> prims.set_sleep_thresholds(np.full((3,), 0.01), indices=np.array([0, 2, 4]))
- set_solver_position_iteration_counts(counts: Union[numpy.ndarray, torch.Tensor, warp.types.array], indices: Optional[Union[numpy.ndarray, List, torch.Tensor, warp.types.array]] = None) None
Set the solver (position) iteration count for the articulations
The solver iteration count determines how accurately contacts, drives, and limits are resolved. Search for Solver Iteration Count in PhysX docs for more details.
Warning
Setting a higher number of iterations may improve the fidelity of the simulation, although it may affect its performance.
- Parameters
counts (Union[np.ndarray, torch.Tensor, wp.array]) – number of iterations for the solver. Shape (M,).
indices (Optional[Union[np.ndarray, List, torch.Tensor, wp.array]], optional) – indices to specify which prims to manipulate. Shape (M,). Where M <= size of the encapsulated prims in the view. Defaults to None (i.e: all prims in the view).
Example:
>>> # set the position iteration count for all envs >>> prims.set_solver_position_iteration_counts(np.full((num_envs,), 64)) >>> >>> # set only the position iteration count for the first, middle and last of the 5 envs >>> prims.set_solver_position_iteration_counts(np.full((3,), 64), indices=np.array([0, 2, 4]))
- set_solver_velocity_iteration_counts(counts: Union[numpy.ndarray, torch.Tensor, warp.types.array], indices: Optional[Union[numpy.ndarray, List, torch.Tensor, warp.types.array]] = None) None
Set the solver (velocity) iteration count for the articulations
The solver iteration count determines how accurately contacts, drives, and limits are resolved. Search for Solver Iteration Count in PhysX docs for more details.
Warning
Setting a higher number of iterations may improve the fidelity of the simulation, although it may affect its performance.
- Parameters
counts (Union[np.ndarray, torch.Tensor, wp.array]) – number of iterations for the solver. Shape (M,).
indices (Optional[Union[np.ndarray, List, torch.Tensor, wp.array]], optional) – indices to specify which prims to manipulate. Shape (M,). Where M <= size of the encapsulated prims in the view. Defaults to None (i.e: all prims in the view).
Example:
>>> # set the velocity iteration count for all envs >>> prims.set_solver_velocity_iteration_counts(np.full((num_envs,), 64)) >>> >>> # set only the velocity iteration count for the first, middle and last of the 5 envs >>> prims.set_solver_velocity_iteration_counts(np.full((3,), 64), indices=np.array([0, 2, 4]))
- set_stabilization_thresholds(thresholds: Union[numpy.ndarray, torch.Tensor, warp.types.array], indices: Optional[Union[numpy.ndarray, List, torch.Tensor, warp.types.array]] = None) None
Set the mass-normalized kinetic energy below which the articulation may participate in stabilization
Search for Stabilization Threshold in PhysX docs for more details
- Parameters
thresholds (Union[np.ndarray, torch.Tensor, wp.array]) – stabilization thresholds to be applied. Shape (M,).
indices (Optional[Union[np.ndarray, List, torch.Tensor, wp.array]], optional) – indices to specify which prims to manipulate. Shape (M,). Where M <= size of the encapsulated prims in the view. Defaults to None (i.e: all prims in the view).
Example:
>>> # set the stabilization threshold for all envs >>> prims.set_stabilization_thresholds(np.full((num_envs,), 0.005)) >>> >>> # set only the stabilization threshold for the first, middle and last of the 5 envs >>> prims.set_stabilization_thresholds(np.full((3,), 0.0051), indices=np.array([0, 2, 4]))
- set_velocities(velocities: Optional[Union[numpy.ndarray, torch.Tensor, warp.types.array]] = None, indices: Optional[Union[numpy.ndarray, list, torch.Tensor, warp.types.array]] = None) None
Set the linear and angular velocities of the prims in the view at once.
The method does this through the PhysX API only. It has to be called after initialization
Warning
This method will immediately set the articulation state
- Parameters
velocities (Optional[Union[np.ndarray, torch.Tensor, wp.array]]) – linear and angular velocities respectively to set the rigid prims to. shape is (M, 6).
indices (Optional[Union[np.ndarray, list, torch.Tensor, wp.array]], optional) – indices to specify which prims to manipulate. Shape (M,). Where M <= size of the encapsulated prims in the view. Defaults to None (i.e: all prims in the view).
Hint
This method belongs to the methods used to set the articulation kinematic state:
set_velocities(set_linear_velocities,set_angular_velocities),set_joint_positions,set_joint_velocities,set_joint_effortsExample:
>>> # set each articulation linear velocity to (1., 1., 1.) and angular velocity to (.1, .1, .1) >>> velocities = np.ones((num_envs, 6)) >>> velocities[:,3:] = 0.1 >>> prims.set_velocities(velocities) >>> >>> # set only the articulation velocities for the first, middle and last of the 5 envs >>> velocities = np.ones((3, 6)) >>> velocities[:,3:] = 0.1 >>> prims.set_velocities(velocities, indices=np.array([0, 2, 4]))
- set_visibilities(visibilities: Union[numpy.ndarray, torch.Tensor, warp.types.array], indices: Optional[Union[numpy.ndarray, list, torch.Tensor, warp.types.array]] = None) None
Set the visibilities of the prims in stage
- Parameters
visibilities (Union[np.ndarray, torch.Tensor, wp.array]) – flag to set the visibilities of the usd prims in stage. Shape (M,). Where M <= size of the encapsulated prims in the view.
indices (Optional[Union[np.ndarray, list, torch.Tensor, wp.array]], optional) – indices to specify which prims to manipulate. Shape (M,). Defaults to None (i.e: all prims in the view).
Example:
>>> # make all prims not visible in the stage >>> prims.set_visibilities(visibilities=[False] * num_envs)
- set_world_poses(positions: Optional[Union[numpy.ndarray, torch.Tensor, warp.types.array]] = None, orientations: Optional[Union[numpy.ndarray, torch.Tensor, warp.types.array]] = None, indices: Optional[Union[numpy.ndarray, list, torch.Tensor, warp.types.array]] = None, usd: bool = True) None
Set poses of prims in the view with respect to the world’s frame.
Warning
This method will change (teleport) the prim poses immediately to the indicated value
- Parameters
positions (Optional[Union[np.ndarray, torch.Tensor, wp.array]], optional) – positions in the world frame of the prim. shape is (M, 3). Defaults to None, which means left unchanged.
orientations (Optional[Union[np.ndarray, torch.Tensor, wp.array]], optional) – quaternion orientations in the world frame of the prims. quaternion is scalar-first (w, x, y, z). shape is (M, 4). Defaults to None, which means left unchanged.
indices (Optional[Union[np.ndarray, list, torch.Tensor, wp.array]], optional) – indices to specify which prims to manipulate. Shape (M,). Where M <= size of the encapsulated prims in the view. Defaults to None (i.e: all prims in the view).
usd (bool, optional) – True to query from usd. Otherwise False to query from Fabric data. Defaults to True.
Hint
This method belongs to the methods used to set the prim state
Example:
>>> # reposition all articulations in row (x-axis) >>> positions = np.zeros((num_envs, 3)) >>> positions[:,0] = np.arange(num_envs) >>> orientations = np.tile(np.array([1.0, 0.0, 0.0, 0.0]), (num_envs, 1)) >>> prims.set_world_poses(positions, orientations) >>> >>> # reposition only the articulations for the first, middle and last of the 5 envs in column (y-axis) >>> positions = np.zeros((3, 3)) >>> positions[:,1] = np.arange(3) >>> orientations = np.tile(np.array([1.0, 0.0, 0.0, 0.0]), (3, 1)) >>> prims.set_world_poses(positions, orientations, indices=np.array([0, 2, 4]))
- switch_control_mode(mode: str, indices: Optional[Union[numpy.ndarray, List, torch.Tensor, warp.types.array]] = None, joint_indices: Optional[Union[numpy.ndarray, List, torch.Tensor, warp.types.array]] = None) None
Switch control mode between
"position","velocity", or"effort"for all jointsThis method will set the implicit Proportional-Derivative (PD) controller’s Kps (stiffnesses) and Kds (dampings), defined via the
set_gainsmethod, of the selected articulations and joints according to the following rule:Control mode
Stiffnesses
Dampings
"position"Kps
Kds
"velocity"0
Kds
"effort"0
0
- Parameters
mode (str) – control mode to switch the articulations specified to. It can be
"position","velocity", or"effort"indices (Optional[Union[np.ndarray, List, torch.Tensor, wp.array]], optional) – indices to specify which prims to manipulate. Shape (M,). Where M <= size of the encapsulated prims in the view. Defaults to None (i.e: all prims in the view).
joint_indices (Optional[Union[np.ndarray, List, torch.Tensor, wp.array]], optional) – joint indices to specify which joints to manipulate. Shape (K,). Where K <= num of dofs. Defaults to None (i.e: all dofs).
Example:
>>> # set 'velocity' as control mode for all joints >>> prims.switch_control_mode("velocity") >>> >>> # set 'effort' as control mode only for the fingers: panda_finger_joint1 (7) and panda_finger_joint2 (8) >>> # for the first, middle and last of the 5 envs >>> prims.switch_control_mode("effort", indices=np.array([0, 2, 4]), joint_indices=np.array([7, 8]))
- switch_dof_control_mode(mode: str, dof_index: int, indices: Optional[Union[numpy.ndarray, List, torch.Tensor, warp.types.array]] = None) None
Switch control mode between
"position","velocity", or"effort"for the specified DOFThis method will set the implicit Proportional-Derivative (PD) controller’s Kps (stiffnesses) and Kds (dampings), defined via the
set_gainsmethod, of the selected DOF according to the following rule:Control mode
Stiffnesses
Dampings
"position"Kps
Kds
"velocity"0
Kds
"effort"0
0
- Parameters
mode (str) – control mode to switch the DOF specified to. It can be
"position","velocity"or"effort"dof_index (int) – dof index to switch the control mode of.
indices (Optional[Union[np.ndarray, List, torch.Tensor, wp.array]], optional) – indices to specify which prims to manipulate. Shape (M,). Where M <= size of the encapsulated prims in the view. Defaults to None (i.e: all prims in the view).
Example:
>>> # set 'velocity' as control mode for the panda_joint1 (0) joint for all envs >>> prims.switch_dof_control_mode("velocity", dof_index=0) >>> >>> # set 'effort' as control mode for the panda_joint1 (0) for the first, middle and last of the 5 envs >>> prims.switch_dof_control_mode("effort", dof_index=0, indices=np.array([0, 2, 4]))
ArticulationController
- class ArticulationController
PD Controller of all degrees of freedom of an articulation, can apply position targets, velocity targets and efforts.
- Checkout the required tutorials at
https://docs.omniverse.nvidia.com/app_isaacsim/app_isaacsim/overview.html
- apply_action(control_actions: omni.isaac.core.utils.types.ArticulationAction) None
[summary]
- Parameters
control_actions (ArticulationAction) – actions to be applied for next physics step.
indices (Optional[Union[list, np.ndarray]], optional) – degree of freedom indices to apply actions to. Defaults to all degrees of freedom.
- Raises
Exception – [description]
- get_applied_action() omni.isaac.core.utils.types.ArticulationAction
- Raises
Exception – [description]
- Returns
Gets last applied action.
- Return type
- get_effort_modes() List[str]
[summary]
- Raises
Exception – [description]
NotImplementedError – [description]
- Returns
[description]
- Return type
np.ndarray
- get_gains() Tuple[numpy.ndarray, numpy.ndarray]
[summary]
- Raises
Exception – [description]
- Returns
[description]
- Return type
Tuple[np.ndarray, np.ndarray]
- get_joint_limits() Tuple[numpy.ndarray, numpy.ndarray]
[summary]
- Raises
Exception – [description]
- Returns
[description]
- Return type
Tuple[np.ndarray, np.ndarray]
- get_max_efforts() numpy.ndarray
[summary]
- Raises
Exception – [description]
- Returns
[description]
- Return type
np.ndarray
- initialize(articulation_view) None
[summary]
- Parameters
articulation_view ([type]) – [description]
- set_effort_modes(mode: str, joint_indices: Optional[Union[numpy.ndarray, list]] = None) None
[summary]
- Parameters
mode (str) – [description]
indices (Optional[Union[np.ndarray, list]], optional) – [description]. Defaults to None.
- Raises
Exception – [description]
Exception – [description]
- set_gains(kps: Optional[numpy.ndarray] = None, kds: Optional[numpy.ndarray] = None, save_to_usd: bool = False) None
[summary]
- Parameters
kps (Optional[np.ndarray], optional) – [description]. Defaults to None.
kds (Optional[np.ndarray], optional) – [description]. Defaults to None.
- Raises
Exception – [description]
- set_max_efforts(values: numpy.ndarray, joint_indices: Optional[Union[numpy.ndarray, list]] = None) None
[summary]
- Parameters
value (float, optional) – [description]. Defaults to None.
indices (Optional[Union[np.ndarray, list]], optional) – [description]. Defaults to None.
- Raises
Exception – [description]
- switch_control_mode(mode: str) None
[summary]
- Parameters
mode (str) – [description]
- Raises
Exception – [description]
- switch_dof_control_mode(dof_index: int, mode: str) None
[summary]
- Parameters
dof_index (int) – [description]
mode (str) – [description]
- Raises
Exception – [description]
Loggers
DataLogger
- class DataLogger
This class takes care of collecting data as well as reading already saved data in order to replay it for instance.
- add_data(data: dict, current_time_step: float, current_time: float) None
Adds data to the log
- Parameters
data (dict) – Dictionary representing the data to be logged at this time index.
current_time_step (float) – time step corresponding to the data collected.
current_time (float) – time in seconds corresponding to the data collected.
- add_data_frame_logging_func(func: Callable[[List[omni.isaac.core.tasks.base_task.BaseTask], omni.isaac.core.scenes.scene.Scene], Dict]) None
- get_data_frame(data_frame_index: int) omni.isaac.core.utils.types.DataFrame
- Parameters
data_frame_index (int) – index of the data frame to retrieve.
- Returns
Data Frame collected/ retrieved at the specified data frame index.
- Return type
- get_num_of_data_frames() int
- Returns
the number of data frames collected/ retrieved in the data logger.
- Return type
int
- is_started() bool
- Returns
True if data collection is started/ resumed. False otherwise.
- Return type
bool
- load(log_path: str) None
Loads data from a json file to read back a previous saved data or to resume recording data from another time step.
- Parameters
log_path (str) – path of the json file to be used to load the data.
- pause() None
Pauses data collection.
- reset() None
Clears the data in the logger.
- save(log_path: str) None
Saves the current data in the logger to a json file
- Parameters
log_path (str) – path of the json file to be used to save the data.
- start() None
Resumes/ starts data collection.
Materials
Visual Material
- class VisualMaterial(name: str, prim_path: str, prim: pxr.Usd.Prim, shaders_list: List[pxr.UsdShade.Shader], material: pxr.UsdShade.Material)
[summary]
- Parameters
name (str) – [description]
prim_path (str) – [description]
prim (Usd.Prim) – [description]
shaders_list (list[UsdShade.Shader]) – [description]
material (UsdShade.Material) – [description]
- property material: pxr.UsdShade.Material
[summary]
- Returns
[description]
- Return type
UsdShade.Material
- property name: str
[summary]
- Returns
[description]
- Return type
str
- property prim: pxr.Usd.Prim
[summary]
- Returns
[description]
- Return type
Usd.Prim
- property prim_path: str
[summary]
- Returns
[description]
- Return type
str
- property shaders_list: List[pxr.UsdShade.Shader]
[summary]
- Returns
[description]
- Return type
[type]
Preview Surface
- class PreviewSurface(prim_path: str, name: str = 'preview_surface', shader: Optional[pxr.UsdShade.Shader] = None, color: Optional[numpy.ndarray] = None, roughness: Optional[float] = None, metallic: Optional[float] = None)
[summary]
- Parameters
prim_path (str) – [description]
name (str, optional) – [description]. Defaults to “preview_surface”.
shader (Optional[UsdShade.Shader], optional) – [description]. Defaults to None.
color (Optional[np.ndarray], optional) – [description]. Defaults to None.
roughness (Optional[float], optional) – [description]. Defaults to None.
metallic (Optional[float], optional) – [description]. Defaults to None.
- get_color() numpy.ndarray
[summary]
- Returns
[description]
- Return type
np.ndarray
- get_metallic() float
[summary]
- Returns
[description]
- Return type
float
- get_roughness() float
[summary]
- Returns
[description]
- Return type
float
- property material: pxr.UsdShade.Material
[summary]
- Returns
[description]
- Return type
UsdShade.Material
- property name: str
[summary]
- Returns
[description]
- Return type
str
- property prim: pxr.Usd.Prim
[summary]
- Returns
[description]
- Return type
Usd.Prim
- property prim_path: str
[summary]
- Returns
[description]
- Return type
str
- set_color(color: numpy.ndarray) None
[summary]
- Parameters
color (np.ndarray) – [description]
- set_metallic(metallic: float) None
[summary]
- Parameters
metallic (float) – [description]
- set_roughness(roughness: float) None
[summary]
- Parameters
roughness (float) – [description]
- property shaders_list: List[pxr.UsdShade.Shader]
[summary]
- Returns
[description]
- Return type
[type]
OmniPBR Material
- class OmniPBR(prim_path: str, name: str = 'omni_pbr', shader: Optional[pxr.UsdShade.Shader] = None, texture_path: Optional[str] = None, texture_scale: Optional[numpy.ndarray] = None, texture_translate: Optional[numpy.ndarray] = None, color: Optional[numpy.ndarray] = None)
[summary]
- Parameters
prim_path (str) – [description]
name (str, optional) – [description]. Defaults to “omni_pbr”.
shader (Optional[UsdShade.Shader], optional) – [description]. Defaults to None.
texture_path (Optional[str], optional) – [description]. Defaults to None.
texture_scale (Optional[np.ndarray], optional) – [description]. Defaults to None.
texture_translate (Optional[np.ndarray, optional) – [description]. Defaults to None.
color (Optional[np.ndarray], optional) – [description]. Defaults to None.
- get_color() numpy.ndarray
[summary]
- Returns
[description]
- Return type
np.ndarray
- get_metallic_constant() float
[summary]
- Returns
[description]
- Return type
float
- get_project_uvw() bool
[summary]
- Returns
[description]
- Return type
bool
- get_reflection_roughness() float
[summary]
- Returns
[description]
- Return type
float
- get_texture() str
[summary]
- Returns
[description]
- Return type
str
- get_texture_scale() numpy.ndarray
[summary]
- Returns
[description]
- Return type
np.ndarray
- get_texture_translate() numpy.ndarray
[summary]
- Returns
[description]
- Return type
np.ndarray
- property material: pxr.UsdShade.Material
[summary]
- Returns
[description]
- Return type
UsdShade.Material
- property name: str
[summary]
- Returns
[description]
- Return type
str
- property prim: pxr.Usd.Prim
[summary]
- Returns
[description]
- Return type
Usd.Prim
- property prim_path: str
[summary]
- Returns
[description]
- Return type
str
- set_color(color: numpy.ndarray) None
[summary]
- Parameters
color (np.ndarray) – [description]
- set_metallic_constant(amount: float) None
[summary]
- Parameters
amount (float) – [description]
- set_project_uvw(flag: bool) None
[summary]
- Parameters
flag (bool) – [description]
- set_reflection_roughness(amount: float) None
[summary]
- Parameters
amount (float) – [description]
- set_texture(path: str) None
[summary]
- Parameters
path (str) – [description]
- set_texture_scale(x: float, y: float) None
[summary]
- Parameters
x (float) – [description]
y (float) – [description]
- set_texture_translate(x: float, y: float) None
[summary]
- Parameters
x (float) – [description]
y (float) – [description]
- property shaders_list: List[pxr.UsdShade.Shader]
[summary]
- Returns
[description]
- Return type
[type]
Omni Glass Material
- class OmniGlass(prim_path: str, name: str = 'omni_glass', shader: Optional[pxr.UsdShade.Shader] = None, color: Optional[numpy.ndarray] = None, ior: Optional[float] = None, depth: Optional[float] = None, thin_walled: Optional[bool] = None)
[summary]
- Parameters
prim_path (str) – [description]
name (str, optional) – [description]. Defaults to “omni_glass”.
shader (Optional[UsdShade.Shader], optional) – [description]. Defaults to None.
color (Optional[np.ndarray], optional) – [description]. Defaults to None.
ior (Optional[float], optional) – [description]. Defaults to None.
depth (Optional[float], optional) – [description]. Defaults to None.
thin_walled (Optional[bool], optional) – [description]. Defaults to None.
- Raises
Exception – [description]
- get_color() Optional[numpy.ndarray]
[summary]
- Returns
[description]
- Return type
np.ndarray
- get_depth() Optional[float]
- get_ior() Optional[float]
- get_thin_walled() Optional[float]
- property material: pxr.UsdShade.Material
[summary]
- Returns
[description]
- Return type
UsdShade.Material
- property name: str
[summary]
- Returns
[description]
- Return type
str
- property prim: pxr.Usd.Prim
[summary]
- Returns
[description]
- Return type
Usd.Prim
- property prim_path: str
[summary]
- Returns
[description]
- Return type
str
- set_color(color: numpy.ndarray) None
[summary]
- Parameters
color (np.ndarray) – [description]
- set_depth(depth: float) None
- set_ior(ior: float) None
- set_thin_walled(thin_walled: float) None
- property shaders_list: List[pxr.UsdShade.Shader]
[summary]
- Returns
[description]
- Return type
[type]
Physics Material
- class PhysicsMaterial(prim_path: str, name: str = 'physics_material', static_friction: Optional[float] = None, dynamic_friction: Optional[float] = None, restitution: Optional[float] = None)
[summary]
- Parameters
prim_path (str) – [description]
name (str, optional) – [description]. Defaults to “physics_material”.
static_friction (Optional[float], optional) – [description]. Defaults to None.
dynamic_friction (Optional[float], optional) – [description]. Defaults to None.
restitution (Optional[float], optional) – [description]. Defaults to None.
- get_dynamic_friction() float
[summary]
- Returns
[description]
- Return type
float
- get_restitution() float
[summary]
- Returns
[description]
- Return type
float
- get_static_friction() float
[summary]
- Returns
[description]
- Return type
float
- property material: pxr.UsdShade.Material
[summary]
- Returns
[description]
- Return type
UsdShade.Material
- property name: str
[summary]
- Returns
[description]
- Return type
str
- property prim: pxr.Usd.Prim
[summary]
- Returns
[description]
- Return type
Usd.Prim
- property prim_path: str
[summary]
- Returns
[description]
- Return type
str
- set_dynamic_friction(friction: float) None
[summary]
- Parameters
friction (float) – [description]
- set_restitution(restitution: float) None
[summary]
- Parameters
restitution (float) – [description]
- set_static_friction(friction: float) None
[summary]
- Parameters
friction (float) – [description]
Particle Material
- class ParticleMaterial(prim_path: str, name: Optional[str] = 'particle_material', friction: Optional[float] = None, particle_friction_scale: Optional[float] = None, damping: Optional[float] = None, viscosity: Optional[float] = None, vorticity_confinement: Optional[float] = None, surface_tension: Optional[float] = None, cohesion: Optional[float] = None, adhesion: Optional[float] = None, particle_adhesion_scale: Optional[float] = None, adhesion_offset_scale: Optional[float] = None, gravity_scale: Optional[float] = None, lift: Optional[float] = None, drag: Optional[float] = None)
A wrapper around position-based-dynamics (PBD) material for particles used to simulate fluids, cloth and inflatables.
Note
Currently, only a single material per particle system is supported which applies to all objects that are associated with the system.
- get_adhesion() float
- Returns
The adhesion for interaction between particles (solid or fluid), and rigids or deformables.
- Return type
float
- get_adhesion_offset_scale() float
- Returns
The adhesion offset scale.
- Return type
float
- get_cohesion() float
- Returns
The cohesion for interaction between fluid particles.
- Return type
float
- get_damping() float
- Returns
The global velocity damping coefficient.
- Return type
float
- get_drag() float
- Returns
The drag coefficient, basic aerodynamic drag model coefficient.
- Return type
float
- get_friction() float
- Returns
The friction coefficient.
- Return type
float
- get_gravity_scale() float
- Returns
The gravitational acceleration scaling factor.
- Return type
float
- get_lift() float
- Returns
The lift coefficient, basic aerodynamic lift model coefficient.
- Return type
float
- get_particle_adhesion_scale() float
- Returns
The particle adhesion scale.
- Return type
float
- get_particle_friction_scale() float
- Returns
The particle friction scale.
- Return type
float
- get_surface_tension() float
- Returns
The surface tension for fluid particles.
- Return type
float
- get_viscosity() float
- Returns
The viscosity.
- Return type
float
- get_vorticity_confinement() float
- Returns
The vorticity confinement for fluid particles.
- Return type
float
- initialize(physics_sim_view=None) None
- is_valid() bool
- Returns
True is the current prim path corresponds to a valid prim in stage. False otherwise.
- Return type
bool
- property material: pxr.UsdShade.Material
Returns: UsdShade.Material: The USD Material object.
- property name: Optional[str]
Returns: str: name given to the prim when instantiating it. Otherwise None.
- post_reset() None
Resets the prim to its default state.
- property prim: pxr.Usd.Prim
Returns: Usd.Prim: The USD prim present.
- property prim_path: str
Returns: str: The stage path to the material.
- set_adhesion(value: float) None
Sets the adhesion for interaction between particles (solid or fluid), and rigid or deformable objects.
Note
Adhesion also applies to solid-solid particle interactions, but is multiplied with the particle adhesion scale.
- Parameters
value (float) – The adhesion. Range: [0, inf), Units: dimensionless
- set_adhesion_offset_scale(value: float) None
Sets the adhesion offset scale.
It defines the offset at which adhesion ceases to take effect. For interactions between particles (fluid or solid), and rigids or deformables, the adhesion offset is defined relative to the rest offset. For solid particle-particle interactions, the adhesion offset is defined relative to the solid rest offset.
- Parameters
value (float) – The adhesion offset scale. Range: [0, inf), Units: dimensionless
- set_cohesion(value: float) None
Sets the cohesion for interaction between fluid particles.
- Parameters
value (float) – The cohesion. Range: [0, inf), Units: dimensionless
- set_damping(value: float) None
Sets the global velocity damping coefficient.
- Parameters
value (float) – The damping coefficient. Range: [0, inf), Units: dimensionless
- set_drag(value: float) None
Sets the drag coefficient, i.e. basic aerodynamic drag model coefficient.
It is useful for cloth and inflatable particle objects.
- Parameters
value (float) – The drag coefficient. Range: [0, inf), Units: dimensionless
- set_friction(value: float) None
Sets the friction coefficient.
The friction takes effect in all interactions between particles and rigids or deformables. For solid particle-particle interactions it is multiplied by the particle friction scale.
- Parameters
value (float) – The friction coefficient. Range: [0, inf), Units: dimensionless
- set_gravity_scale(value: float) None
Sets the gravitational acceleration scaling factor.
It can be used to approximate lighter-than-air inflatable. For example (-1.0 would invert gravity).
- Parameters
value (float) – The gravity scale. Range: (-inf , inf), Units: dimensionless
- set_lift(value: float) None
Sets the lift coefficient, i.e. basic aerodynamic lift model coefficient.
It is useful for cloth and inflatable particle objects.
- Parameters
value (float) – The lift coefficient. Range: [0, inf), Units: dimensionless
- set_particle_adhesion_scale(value: float) None
Sets the particle adhesion scale.
This coefficient scales the adhesion for solid particle-particle interaction.
- Parameters
value (float) – The adhesion scale. Range: [0, inf), Units: dimensionless
- set_particle_friction_scale(value: float) None
Sets the particle friction scale.
The coefficient that scales friction for solid particle-particle interaction.
- Parameters
value (float) – The particle friction scale. Range: [0, inf), Units: dimensionless
- set_surface_tension(value: float) None
Sets the surface tension for fluid particles.
- Parameters
value (float) – The surface tension. Range: [0, inf), Units: 1 / (distance * distance * distance)
- set_viscosity(value: float) None
Sets the viscosity for fluid particles.
- Parameters
value (float) – The viscosity. Range: [0, inf), Units: dimensionless
- set_vorticity_confinement(value: float) None
Sets the vorticity confinement for fluid particles.
This helps prevent energy loss due to numerical solver by adding vortex-like accelerations to the particles.
- Parameters
value (float) – The vorticity confinement. Range: [0, inf), Units: dimensionless
Particle Material View
- class ParticleMaterialView(prim_paths_expr: str, name: str = 'particle_material_view', frictions: Optional[Union[numpy.ndarray, torch.Tensor]] = None, particle_friction_scales: Optional[Union[numpy.ndarray, torch.Tensor]] = None, dampings: Optional[Union[numpy.ndarray, torch.Tensor]] = None, viscosities: Optional[Union[numpy.ndarray, torch.Tensor]] = None, vorticity_confinements: Optional[Union[numpy.ndarray, torch.Tensor]] = None, surface_tensions: Optional[Union[numpy.ndarray, torch.Tensor]] = None, cohesions: Optional[Union[numpy.ndarray, torch.Tensor]] = None, adhesions: Optional[Union[numpy.ndarray, torch.Tensor]] = None, particle_adhesion_scales: Optional[Union[numpy.ndarray, torch.Tensor]] = None, adhesion_offset_scales: Optional[Union[numpy.ndarray, torch.Tensor]] = None, gravity_scales: Optional[Union[numpy.ndarray, torch.Tensor]] = None, lifts: Optional[Union[numpy.ndarray, torch.Tensor]] = None, drags: Optional[Union[numpy.ndarray, torch.Tensor]] = None)
The view class to deal with particleMaterial prims. Provides high level functions to deal with particle material (1 or more particle materials) as well as its attributes/ properties. This object wraps all matching materials found at the regex provided at the prim_paths_expr. This object wraps all matching materials Prims found at the regex provided at the prim_paths_expr.
- property count: int
Returns: int: number of rigid shapes for the prims in the view.
- get_adhesion_offset_scales(indices: Optional[Union[numpy.ndarray, list, torch.Tensor]] = None, clone: bool = True) Union[numpy.ndarray, torch.Tensor]
Gets the adhesion offset scale of materials indicated by the indices.
- Parameters
indices (Optional[Union[np.ndarray, list, torch.Tensor]], optional) – indices to specify which material prims to query. Shape (M,). Where M <= size of the encapsulated prims in the view. Defaults to None (i.e: all prims in the view).
clone (bool, optional) – True to return a clone of the internal buffer. Otherwise False. Defaults to True.
- Returns
adhesion offset scale tensor with shape (M, )
- Return type
Union[np.ndarray, torch.Tensor]
- get_adhesions(indices: Optional[Union[numpy.ndarray, list, torch.Tensor]] = None, clone: bool = True) Union[numpy.ndarray, torch.Tensor]
Gets the adhesion of materials indicated by the indices.
- Parameters
indices (Optional[Union[np.ndarray, list, torch.Tensor]], optional) – indices to specify which material prims to query. Shape (M,). Where M <= size of the encapsulated prims in the view. Defaults to None (i.e: all prims in the view).
clone (bool, optional) – True to return a clone of the internal buffer. Otherwise False. Defaults to True.
- Returns
adhesion tensor with shape (M, )
- Return type
Union[np.ndarray, torch.Tensor]
- get_cohesions(indices: Optional[Union[numpy.ndarray, list, torch.Tensor]] = None, clone: bool = True) Union[numpy.ndarray, torch.Tensor]
Gets the cohesion of materials indicated by the indices.
- Parameters
indices (Optional[Union[np.ndarray, list, torch.Tensor]], optional) – indices to specify which material prims to query. Shape (M,). Where M <= size of the encapsulated prims in the view. Defaults to None (i.e: all prims in the view).
clone (bool, optional) – True to return a clone of the internal buffer. Otherwise False. Defaults to True.
- Returns
cohesion tensor with shape (M, )
- Return type
Union[np.ndarray, torch.Tensor]
- get_dampings(indices: Optional[Union[numpy.ndarray, list, torch.Tensor]] = None, clone: bool = True) Union[numpy.ndarray, torch.Tensor]
Gets the dampings of materials indicated by the indices.
- Parameters
indices (Optional[Union[np.ndarray, list, torch.Tensor]], optional) – indices to specify which material prims to query. Shape (M,). Where M <= size of the encapsulated prims in the view. Defaults to None (i.e: all prims in the view).
clone (bool, optional) – True to return a clone of the internal buffer. Otherwise False. Defaults to True.
- Returns
dampings tensor with shape (M, )
- Return type
Union[np.ndarray, torch.Tensor]
- get_drags(indices: Optional[Union[numpy.ndarray, list, torch.Tensor]] = None, clone: bool = True) Union[numpy.ndarray, torch.Tensor]
Gets the drags of materials indicated by the indices.
- Parameters
indices (Optional[Union[np.ndarray, list, torch.Tensor]], optional) – indices to specify which material prims to query. Shape (M,). Where M <= size of the encapsulated prims in the view. Defaults to None (i.e: all prims in the view).
clone (bool, optional) – True to return a clone of the internal buffer. Otherwise False. Defaults to True.
- Returns
drag tensor with shape (M, )
- Return type
Union[np.ndarray, torch.Tensor]
- get_frictions(indices: Optional[Union[numpy.ndarray, list, torch.Tensor]] = None, clone: bool = True) Union[numpy.ndarray, torch.Tensor]
Gets the friction of materials indicated by the indices.
- Parameters
indices (Optional[Union[np.ndarray, list, torch.Tensor]], optional) – indices to specify which material prims to query. Shape (M,). Where M <= size of the encapsulated prims in the view. Defaults to None (i.e: all prims in the view).
clone (bool, optional) – True to return a clone of the internal buffer. Otherwise False. Defaults to True.
- Returns
friction tensor with shape (M, )
- Return type
Union[np.ndarray, torch.Tensor]
- get_gravity_scales(indices: Optional[Union[numpy.ndarray, list, torch.Tensor]] = None, clone: bool = True) Union[numpy.ndarray, torch.Tensor]
Gets the gravity scale of materials indicated by the indices.
- Parameters
indices (Optional[Union[np.ndarray, list, torch.Tensor]], optional) – indices to specify which material prims to query. Shape (M,). Where M <= size of the encapsulated prims in the view. Defaults to None (i.e: all prims in the view).
clone (bool, optional) – True to return a clone of the internal buffer. Otherwise False. Defaults to True.
- Returns
gravity scale tensor with shape (M, )
- Return type
Union[np.ndarray, torch.Tensor]
- get_lifts(indices: Optional[Union[numpy.ndarray, list, torch.Tensor]] = None, clone: bool = True) Union[numpy.ndarray, torch.Tensor]
Gets the lifts of materials indicated by the indices.
- Parameters
indices (Optional[Union[np.ndarray, list, torch.Tensor]], optional) – indices to specify which material prims to query. Shape (M,). Where M <= size of the encapsulated prims in the view. Defaults to None (i.e: all prims in the view).
clone (bool, optional) – True to return a clone of the internal buffer. Otherwise False. Defaults to True.
- Returns
lift tensor with shape (M, )
- Return type
Union[np.ndarray, torch.Tensor]
- get_particle_adhesion_scales(indices: Optional[Union[numpy.ndarray, list, torch.Tensor]] = None, clone: bool = True) Union[numpy.ndarray, torch.Tensor]
Gets the adhesion scale of materials indicated by the indices.
- Parameters
indices (Optional[Union[np.ndarray, list, torch.Tensor]], optional) – indices to specify which material prims to query. Shape (M,). Where M <= size of the encapsulated prims in the view. Defaults to None (i.e: all prims in the view).
clone (bool, optional) – True to return a clone of the internal buffer. Otherwise False. Defaults to True.
- Returns
adhesion scale tensor with shape (M, )
- Return type
Union[np.ndarray, torch.Tensor]
- get_particle_friction_scales(indices: Optional[Union[numpy.ndarray, list, torch.Tensor]] = None, clone: bool = True) Union[numpy.ndarray, torch.Tensor]
Gets the particle friction scale of materials indicated by the indices.
- Parameters
indices (Optional[Union[np.ndarray, list, torch.Tensor]], optional) – indices to specify which material prims to query. Shape (M,). Where M <= size of the encapsulated prims in the view. Defaults to None (i.e: all prims in the view).
clone (bool, optional) – True to return a clone of the internal buffer. Otherwise False. Defaults to True.
- Returns
particle friction scale tensor with shape (M, )
- Return type
Union[np.ndarray, torch.Tensor]
- get_surface_tensions(indices: Optional[Union[numpy.ndarray, list, torch.Tensor]] = None, clone: bool = True) Union[numpy.ndarray, torch.Tensor]
Gets the surface tension of materials indicated by the indices.
- Parameters
indices (Optional[Union[np.ndarray, list, torch.Tensor]], optional) – indices to specify which material prims to query. Shape (M,). Where M <= size of the encapsulated prims in the view. Defaults to None (i.e: all prims in the view).
clone (bool, optional) – True to return a clone of the internal buffer. Otherwise False. Defaults to True.
- Returns
surface tension tensor with shape (M, )
- Return type
Union[np.ndarray, torch.Tensor]
- get_viscosities(indices: Optional[Union[numpy.ndarray, list, torch.Tensor]] = None, clone: bool = True) Union[numpy.ndarray, torch.Tensor]
Gets the viscosity of materials indicated by the indices.
- Parameters
indices (Optional[Union[np.ndarray, list, torch.Tensor]], optional) – indices to specify which material prims to query. Shape (M,). Where M <= size of the encapsulated prims in the view. Defaults to None (i.e: all prims in the view).
clone (bool, optional) – True to return a clone of the internal buffer. Otherwise False. Defaults to True.
- Returns
viscosity tensor with shape (M, )
- Return type
Union[np.ndarray, torch.Tensor]
- get_vorticity_confinements(indices: Optional[Union[numpy.ndarray, list, torch.Tensor]] = None, clone: bool = True) Union[numpy.ndarray, torch.Tensor]
Gets the vorticity confinement of materials indicated by the indices.
- Parameters
indices (Optional[Union[np.ndarray, list, torch.Tensor]], optional) – indices to specify which material prims to query. Shape (M,). Where M <= size of the encapsulated prims in the view. Defaults to None (i.e: all prims in the view).
clone (bool, optional) – True to return a clone of the internal buffer. Otherwise False. Defaults to True.
- Returns
vorticity confinement tensor with shape (M, )
- Return type
Union[np.ndarray, torch.Tensor]
- initialize(physics_sim_view: Optional[omni.physics.tensors.bindings._physicsTensors.SimulationView] = None) None
Create a physics simulation view if not passed and creates a rigid body view in physX.
- Parameters
physics_sim_view (omni.physics.tensors.SimulationView, optional) – current physics simulation view. Defaults to None.
- is_physics_handle_valid() bool
- Returns
True if the physics handle of the view is valid (i.e physics is initialized for the view). Otherwise False.
- Return type
bool
- is_valid(indices: Optional[Union[numpy.ndarray, list, torch.Tensor]] = None) bool
- Parameters
indices (Optional[Union[np.ndarray, list, torch.Tensor]], optional) – indices to specify which prims to query. Shape (M,). Where M <= size of the encapsulated prims in the view. Defaults to None (i.e: all prims in the view).
- Returns
True if all prim paths specified in the view correspond to a valid prim in stage. False otherwise.
- Return type
bool
- property name: str
Returns: str: name given to the view when instantiating it.
- post_reset() None
Resets the particles to their initial states.
- set_adhesion_offset_scales(values: Optional[Union[numpy.ndarray, torch.Tensor]], indices: Optional[Union[numpy.ndarray, list, torch.Tensor]] = None) None
Sets the adhesion offset scale for the material prims indicated by the indices.
- Parameters
values (Optional[Union[np.ndarray, torch.Tensor]], optional) – material adhesion offset scale tensor with the shape (M, ).
indices (Optional[Union[np.ndarray, list, torch.Tensor]], optional) – indices to specify which material prims to manipulate. Shape (M,). Where M <= size of the encapsulated prims in the view. Defaults to None (i.e: all prims in the view).
- set_adhesions(values: Optional[Union[numpy.ndarray, torch.Tensor]], indices: Optional[Union[numpy.ndarray, list, torch.Tensor]] = None) None
Sets the particle adhesion for the material prims indicated by the indices.
- Parameters
values (Optional[Union[np.ndarray, torch.Tensor]], optional) – material particle adhesion scale tensor with the shape (M, ).
indices (Optional[Union[np.ndarray, list, torch.Tensor]], optional) – indices to specify which material prims to manipulate. Shape (M,). Where M <= size of the encapsulated prims in the view. Defaults to None (i.e: all prims in the view).
- set_cohesions(values: Optional[Union[numpy.ndarray, torch.Tensor]], indices: Optional[Union[numpy.ndarray, list, torch.Tensor]] = None) None
Sets the particle cohesion for the material prims indicated by the indices.
- Parameters
values (Optional[Union[np.ndarray, torch.Tensor]], optional) – material particle cohesion scale tensor with the shape (M, ).
indices (Optional[Union[np.ndarray, list, torch.Tensor]], optional) – indices to specify which material prims to manipulate. Shape (M,). Where M <= size of the encapsulated prims in the view. Defaults to None (i.e: all prims in the view).
- set_dampings(values: Optional[Union[numpy.ndarray, torch.Tensor]], indices: Optional[Union[numpy.ndarray, list, torch.Tensor]] = None) None
Sets the dampings for the material prims indicated by the indices.
- Parameters
values (Optional[Union[np.ndarray, torch.Tensor]], optional) – material damping tensor with the shape (M, ).
indices (Optional[Union[np.ndarray, list, torch.Tensor]], optional) – indices to specify which material prims to manipulate. Shape (M,). Where M <= size of the encapsulated prims in the view. Defaults to None (i.e: all prims in the view).
- set_drags(values: Optional[Union[numpy.ndarray, torch.Tensor]], indices: Optional[Union[numpy.ndarray, list, torch.Tensor]] = None) None
Sets the drags for the material prims indicated by the indices.
- Parameters
values (Optional[Union[np.ndarray, torch.Tensor]], optional) – material drag tensor with the shape (M, ).
indices (Optional[Union[np.ndarray, list, torch.Tensor]], optional) – indices to specify which material prims to manipulate. Shape (M,). Where M <= size of the encapsulated prims in the view. Defaults to None (i.e: all prims in the view).
- set_frictions(values: Optional[Union[numpy.ndarray, torch.Tensor]], indices: Optional[Union[numpy.ndarray, list, torch.Tensor]] = None) None
Sets the friction for the material prims indicated by the indices.
- Parameters
values (Optional[Union[np.ndarray, torch.Tensor]], optional) – material friction tensor with the shape (M, ).
indices (Optional[Union[np.ndarray, list, torch.Tensor]], optional) – indices to specify which material prims to manipulate. Shape (M,). Where M <= size of the encapsulated prims in the view. Defaults to None (i.e: all prims in the view).
- set_gravity_scales(values: Optional[Union[numpy.ndarray, torch.Tensor]], indices: Optional[Union[numpy.ndarray, list, torch.Tensor]] = None) None
Sets the gravity scale for the material prims indicated by the indices.
- Parameters
values (Optional[Union[np.ndarray, torch.Tensor]], optional) – material gravity scale tensor with the shape (M, ).
indices (Optional[Union[np.ndarray, list, torch.Tensor]], optional) – indices to specify which material prims to manipulate. Shape (M,). Where M <= size of the encapsulated prims in the view. Defaults to None (i.e: all prims in the view).
- set_lifts(values: Optional[Union[numpy.ndarray, torch.Tensor]], indices: Optional[Union[numpy.ndarray, list, torch.Tensor]] = None) None
Sets the lifts for the material prims indicated by the indices.
- Parameters
values (Optional[Union[np.ndarray, torch.Tensor]], optional) – material lift tensor with the shape (M, ).
indices (Optional[Union[np.ndarray, list, torch.Tensor]], optional) – indices to specify which material prims to manipulate. Shape (M,). Where M <= size of the encapsulated prims in the view. Defaults to None (i.e: all prims in the view).
- set_particle_adhesion_scales(values: Optional[Union[numpy.ndarray, torch.Tensor]], indices: Optional[Union[numpy.ndarray, list, torch.Tensor]] = None) None
Sets the particle adhesion for the material prims indicated by the indices.
- Parameters
values (Optional[Union[np.ndarray, torch.Tensor]], optional) – material particle adhesion scale tensor with the shape (M, ).
indices (Optional[Union[np.ndarray, list, torch.Tensor]], optional) – indices to specify which material prims to manipulate. Shape (M,). Where M <= size of the encapsulated prims in the view. Defaults to None (i.e: all prims in the view).
- set_particle_friction_scales(values: Optional[Union[numpy.ndarray, torch.Tensor]], indices: Optional[Union[numpy.ndarray, list, torch.Tensor]] = None) None
Sets the particle friction scale for the material prims indicated by the indices.
- Parameters
values (Optional[Union[np.ndarray, torch.Tensor]], optional) – material particle friction scale tensor with the shape (M, ).
indices (Optional[Union[np.ndarray, list, torch.Tensor]], optional) – indices to specify which material prims to manipulate. Shape (M,). Where M <= size of the encapsulated prims in the view. Defaults to None (i.e: all prims in the view).
- set_surface_tensions(values: Optional[Union[numpy.ndarray, torch.Tensor]], indices: Optional[Union[numpy.ndarray, list, torch.Tensor]] = None) None
Sets the particle surface tension for the material prims indicated by the indices.
- Parameters
values (Optional[Union[np.ndarray, torch.Tensor]], optional) – material particle surface tension scale tensor with the shape (M, ).
indices (Optional[Union[np.ndarray, list, torch.Tensor]], optional) – indices to specify which material prims to manipulate. Shape (M,). Where M <= size of the encapsulated prims in the view. Defaults to None (i.e: all prims in the view).
- set_viscosities(values: Optional[Union[numpy.ndarray, torch.Tensor]], indices: Optional[Union[numpy.ndarray, list, torch.Tensor]] = None) None
Sets the particle viscosity for the material prims indicated by the indices.
- Parameters
values (Optional[Union[np.ndarray, torch.Tensor]], optional) – material particle viscosity scale tensor with the shape (M, ).
indices (Optional[Union[np.ndarray, list, torch.Tensor]], optional) – indices to specify which material prims to manipulate. Shape (M,). Where M <= size of the encapsulated prims in the view. Defaults to None (i.e: all prims in the view).
- set_vorticity_confinements(values: Optional[Union[numpy.ndarray, torch.Tensor]], indices: Optional[Union[numpy.ndarray, list, torch.Tensor]] = None) None
Sets the vorticity confinement for the material prims indicated by the indices.
- Parameters
values (Optional[Union[np.ndarray, torch.Tensor]], optional) – material particle vorticity confinement scale tensor with the shape (M, ).
indices (Optional[Union[np.ndarray, list, torch.Tensor]], optional) – indices to specify which material prims to manipulate. Shape (M,). Where M <= size of the encapsulated prims in the view. Defaults to None (i.e: all prims in the view).
Deformable Material
- class DeformableMaterial(prim_path: str, name: Optional[str] = 'deformable_material', dynamic_friction: Optional[float] = None, youngs_modulus: Optional[float] = None, poissons_ratio: Optional[float] = None, elasticity_damping: Optional[float] = None, damping_scale: Optional[float] = None)
A wrapper around deformable material used to simulate soft bodies.
- get_damping_scale() float
- Returns
The damping scale coefficient.
- Return type
float
- get_dynamic_friction() float
- Returns
The dynamic friction coefficient.
- Return type
float
- get_elasticity_damping() float
- Returns
The elasticity damping coefficient.
- Return type
float
- get_poissons_ratio() float
- Returns
The poissons ratio.
- Return type
float
- get_youngs_modululs() float
- Returns
The youngs modululs coefficient.
- Return type
float
- initialize(physics_sim_view=None) None
- is_valid() bool
- Returns
True is the current prim path corresponds to a valid prim in stage. False otherwise.
- Return type
bool
- property material: pxr.UsdShade.Material
Returns: UsdShade.Material: The USD Material object.
- property name: Optional[str]
Returns: str: name given to the prim when instantiating it. Otherwise None.
- post_reset() None
Resets the prim to its default state.
- property prim: pxr.Usd.Prim
Returns: Usd.Prim: The USD prim present.
- property prim_path: str
Returns: str: The stage path to the material.
- set_damping_scale(value: float) None
Sets the damping scale coefficient.
- Parameters
value (float) – The damping scale coefficient Range: [0, inf)
- set_dynamic_friction(value: float) None
Sets the dynamic_friction coefficient.
The dynamic_friction takes effect in all interactions between particles and rigids or deformables. For solid particle-particle interactions it is multiplied by the particle dynamic_friction scale.
- Parameters
value (float) – The dynamic_friction coefficient. Range: [0, inf), Units: dimensionless
- set_elasticity_damping(value: float) None
Sets the global velocity elasticity damping coefficient.
- Parameters
value (float) – The elasticity damping coefficient. Range: [0, inf), Units: dimensionless
- set_poissons_ratio(value: float) None
Sets the poissons ratio coefficient
- Parameters
value (float) – The poissons ratio. Range: (0 , 0.5)
- set_youngs_modululs(value: float) None
Sets the youngs_modululs for fluid particles.
- Parameters
value (float) – The youngs_modululs. Range: [0, inf)
Deformable Material View
- class DeformableMaterialView(prim_paths_expr: str, name: str = 'deformable_material_view', dynamic_frictions: Optional[Union[numpy.ndarray, torch.Tensor]] = None, youngs_moduli: Optional[Union[numpy.ndarray, torch.Tensor]] = None, poissons_ratios: Optional[Union[numpy.ndarray, torch.Tensor]] = None, elasticity_dampings: Optional[Union[numpy.ndarray, torch.Tensor]] = None, damping_scales: Optional[Union[numpy.ndarray, torch.Tensor]] = None)
The view class to deal with deformableMaterial prims. Provides high level functions to deal with deformable material (1 or more deformable materials) as well as its attributes/ properties. This object wraps all matching materials found at the regex provided at the prim_paths_expr. This object wraps all matching materials Prims found at the regex provided at the prim_paths_expr.
- property count: int
Returns: int: number of rigid shapes for the prims in the view.
- get_damping_scales(indices: Optional[Union[numpy.ndarray, list, torch.Tensor]] = None, clone: bool = True) Union[numpy.ndarray, torch.Tensor]
Gets the damping scale of materials indicated by the indices.
- Parameters
indices (Optional[Union[np.ndarray, list, torch.Tensor]], optional) – indices to specify which material prims to query. Shape (M,). Where M <= size of the encapsulated prims in the view. Defaults to None (i.e: all prims in the view).
clone (bool, optional) – True to return a clone of the internal buffer. Otherwise False. Defaults to True.
- Returns
damping scale tensor with shape (M, )
- Return type
Union[np.ndarray, torch.Tensor]
- get_dynamic_frictions(indices: Optional[Union[numpy.ndarray, list, torch.Tensor]] = None, clone: bool = True) Union[numpy.ndarray, torch.Tensor]
Gets the dynamic friction of materials indicated by the indices.
- Parameters
indices (Optional[Union[np.ndarray, list, torch.Tensor]], optional) – indices to specify which material prims to query. Shape (M,). Where M <= size of the encapsulated prims in the view. Defaults to None (i.e: all prims in the view).
clone (bool, optional) – True to return a clone of the internal buffer. Otherwise False. Defaults to True.
- Returns
dynamic friction tensor with shape (M, )
- Return type
Union[np.ndarray, torch.Tensor]
- get_elasticity_dampings(indices: Optional[Union[numpy.ndarray, list, torch.Tensor]] = None, clone: bool = True) Union[numpy.ndarray, torch.Tensor]
Gets the elasticity dampings of materials indicated by the indices.
- Parameters
indices (Optional[Union[np.ndarray, list, torch.Tensor]], optional) – indices to specify which material prims to query. Shape (M,). Where M <= size of the encapsulated prims in the view. Defaults to None (i.e: all prims in the view).
clone (bool, optional) – True to return a clone of the internal buffer. Otherwise False. Defaults to True.
- Returns
elasticity dampings tensor with shape (M, )
- Return type
Union[np.ndarray, torch.Tensor]
- get_poissons_ratios(indices: Optional[Union[numpy.ndarray, list, torch.Tensor]] = None, clone: bool = True) Union[numpy.ndarray, torch.Tensor]
Gets the poissons ratios of materials indicated by the indices.
- Parameters
indices (Optional[Union[np.ndarray, list, torch.Tensor]], optional) – indices to specify which material prims to query. Shape (M,). Where M <= size of the encapsulated prims in the view. Defaults to None (i.e: all prims in the view).
clone (bool, optional) – True to return a clone of the internal buffer. Otherwise False. Defaults to True.
- Returns
poissons ratio tensor with shape (M, )
- Return type
Union[np.ndarray, torch.Tensor]
- get_youngs_moduli(indices: Optional[Union[numpy.ndarray, list, torch.Tensor]] = None, clone: bool = True) Union[numpy.ndarray, torch.Tensor]
Gets the Youngs moduli of materials indicated by the indices.
- Parameters
indices (Optional[Union[np.ndarray, list, torch.Tensor]], optional) – indices to specify which material prims to query. Shape (M,). Where M <= size of the encapsulated prims in the view. Defaults to None (i.e: all prims in the view).
clone (bool, optional) – True to return a clone of the internal buffer. Otherwise False. Defaults to True.
- Returns
Youngs moduli tensor with shape (M, )
- Return type
Union[np.ndarray, torch.Tensor]
- initialize(physics_sim_view: Optional[omni.physics.tensors.bindings._physicsTensors.SimulationView] = None) None
Create a physics simulation view if not passed and creates a rigid body view in physX.
- Parameters
physics_sim_view (omni.physics.tensors.SimulationView, optional) – current physics simulation view. Defaults to None.
- is_physics_handle_valid() bool
- Returns
True if the physics handle of the view is valid (i.e physics is initialized for the view). Otherwise False.
- Return type
bool
- is_valid(indices: Optional[Union[numpy.ndarray, list, torch.Tensor]] = None) bool
- Parameters
indices (Optional[Union[np.ndarray, list, torch.Tensor]], optional) – indices to specify which prims to query. Shape (M,). Where M <= size of the encapsulated prims in the view. Defaults to None (i.e: all prims in the view).
- Returns
True if all prim paths specified in the view correspond to a valid prim in stage. False otherwise.
- Return type
bool
- property name: str
Returns: str: name given to the view when instantiating it.
- post_reset() None
Resets the deformables to their initial states.
- set_damping_scales(values: Optional[Union[numpy.ndarray, torch.Tensor]], indices: Optional[Union[numpy.ndarray, list, torch.Tensor]] = None) None
Sets the damping scale for the material prims indicated by the indices.
- Parameters
values (Optional[Union[np.ndarray, torch.Tensor]], optional) – material damping scale tensor with the shape (M, ).
indices (Optional[Union[np.ndarray, list, torch.Tensor]], optional) – indices to specify which material prims to manipulate. Shape (M,). Where M <= size of the encapsulated prims in the view. Defaults to None (i.e: all prims in the view).
- set_dynamic_frictions(values: Optional[Union[numpy.ndarray, torch.Tensor]], indices: Optional[Union[numpy.ndarray, list, torch.Tensor]] = None) None
Sets the dynamic friction for the material prims indicated by the indices.
- Parameters
values (Optional[Union[np.ndarray, torch.Tensor]], optional) – material dynamic friction tensor with the shape (M, ).
indices (Optional[Union[np.ndarray, list, torch.Tensor]], optional) – indices to specify which material prims to manipulate. Shape (M,). Where M <= size of the encapsulated prims in the view. Defaults to None (i.e: all prims in the view).
- set_elasticity_dampings(values: Optional[Union[numpy.ndarray, torch.Tensor]], indices: Optional[Union[numpy.ndarray, list, torch.Tensor]] = None) None
Sets the elasticity_dampings for the material prims indicated by the indices.
- Parameters
values (Optional[Union[np.ndarray, torch.Tensor]], optional) – material damping tensor with the shape (M, ).
indices (Optional[Union[np.ndarray, list, torch.Tensor]], optional) – indices to specify which material prims to manipulate. Shape (M,). Where M <= size of the encapsulated prims in the view. Defaults to None (i.e: all prims in the view).
- set_poissons_ratios(values: Optional[Union[numpy.ndarray, torch.Tensor]], indices: Optional[Union[numpy.ndarray, list, torch.Tensor]] = None) None
Sets the poissons ratios for the material prims indicated by the indices.
- Parameters
values (Optional[Union[np.ndarray, torch.Tensor]], optional) – material poissons ratio tensor with the shape (M, ).
indices (Optional[Union[np.ndarray, list, torch.Tensor]], optional) – indices to specify which material prims to manipulate. Shape (M,). Where M <= size of the encapsulated prims in the view. Defaults to None (i.e: all prims in the view).
- set_youngs_moduli(values: Optional[Union[numpy.ndarray, torch.Tensor]], indices: Optional[Union[numpy.ndarray, list, torch.Tensor]] = None) None
Sets the youngs moduli for the material prims indicated by the indices.
- Parameters
values (Optional[Union[np.ndarray, torch.Tensor]], optional) – material drag tensor with the shape (M, ).
indices (Optional[Union[np.ndarray, list, torch.Tensor]], optional) – indices to specify which material prims to manipulate. Shape (M,). Where M <= size of the encapsulated prims in the view. Defaults to None (i.e: all prims in the view).
Objects
Modules to create/encapsulate visual, fixed, and dynamic shapes (Capsule, Cone, Cuboid, Cylinder, Sphere) as well as ground planes
Ground Plane
- class GroundPlane(prim_path: str, name: str = 'ground_plane', size: Optional[float] = None, z_position: Optional[float] = None, scale: Optional[numpy.ndarray] = None, visible: Optional[bool] = None, color: Optional[numpy.ndarray] = None, physics_material: Optional[omni.isaac.core.materials.physics_material.PhysicsMaterial] = None, visual_material: Optional[omni.isaac.core.materials.visual_material.VisualMaterial] = None)
High level wrapper to create/encapsulate a ground plane
- Parameters
prim_path (str) – prim path of the Prim to encapsulate or create
name (str, optional) – shortname to be used as a key by Scene class. Note: needs to be unique if the object is added to the Scene. Defaults to “ground_plane”.
size (Optional[float], optional) – length of each edge. Defaults to 5000.0.
z_position (float, optional) – ground plane position in the z-axis. Defaults to 0.
scale (Optional[np.ndarray], optional) – local scale to be applied to the prim’s dimensions. Defaults to None.
visible (bool, optional) – set to false for an invisible prim in the stage while rendering. Defaults to True.
color (Optional[np.ndarray], optional) – color of the visual plane. Defaults to None.
physics_material_path (Optional[PhysicsMaterial], optional) – path of the physics material to be applied to the held prim. Defaults to None. If not specified, a default physics material will be added.
visual_material (Optional[VisualMaterial], optional) – visual material to be applied to the held prim. Defaults to None. If not specified, a default visual material will be added.
static_friction (float, optional) – static friction coefficient. Defaults to 0.5.
dynamic_friction (float, optional) – dynamic friction coefficient. Defaults to 0.5.
restitution (float, optional) – restitution coefficient. Defaults to 0.8.
Example:
>>> from omni.isaac.core.objects import GroundPlane >>> import numpy as np >>> >>> # create a ground plane placed at 0 in the z-axis >>> plane = GroundPlane(prim_path="/World/GroundPlane", z_position=0) >>> plane <omni.isaac.core.objects.ground_plane.GroundPlane object at 0x7f15d003fb50>
- apply_physics_material(physics_material: omni.isaac.core.materials.physics_material.PhysicsMaterial, weaker_than_descendants: bool = False)
Used to apply physics material to the held prim and optionally its descendants.
- Parameters
physics_material (PhysicsMaterial) – physics material to be applied to the held prim. This where you want to define friction, restitution..etc. Note: if a physics material is not defined, the defaults will be used from PhysX.
weaker_than_descendants (bool, optional) – True if the material shouldn’t override the descendants materials, otherwise False. Defaults to False.
Example:
>>> from omni.isaac.core.materials import PhysicsMaterial >>> >>> # create a rigid body physical material >>> material = PhysicsMaterial( ... prim_path="/World/physics_material/aluminum", # path to the material prim to create ... dynamic_friction=0.4, ... static_friction=1.1, ... restitution=0.1 ... ) >>> plane.apply_physics_material(material)
- property collision_geometry_prim: omni.isaac.core.prims.geometry_prim.GeometryPrim
- Returns
wrapped object as a GeometryPrim
- Return type
Example:
>>> plane.collision_geometry_prim <omni.isaac.core.prims.geometry_prim.GeometryPrim object at 0x7f15ff3461a0>
- get_applied_physics_material() omni.isaac.core.materials.physics_material.PhysicsMaterial
Returns the current applied physics material in case it was applied using apply_physics_material or not.
- Returns
the current applied physics material.
- Return type
Example:
>>> plane.get_applied_physics_material() <omni.isaac.core.materials.physics_material.PhysicsMaterial object at 0x7f517ff62920>
- get_default_state() omni.isaac.core.utils.types.XFormPrimState
Get the default prim states (spatial position and orientation).
- Returns
an object that contains the default state of the prim (position and orientation)
- Return type
Example:
>>> state = plane.get_default_state() >>> state <omni.isaac.core.utils.types.XFormPrimState object at 0x7f6efff41cf0> >>> >>> state.position [0. 0. 0.] >>> state.orientation [1. 0. 0. 0.]
- get_world_pose() Tuple[numpy.ndarray, numpy.ndarray]
Get prim’s pose with respect to the world’s frame
- Returns
first index is the position in the world frame (with shape (3, )). Second index is quaternion orientation (with shape (4, )) in the world frame
- Return type
Tuple[np.ndarray, np.ndarray]
Example:
>>> # if the prim is in position (0.0, 0.0, 0.0) with respect to the world frame >>> position, orientation = prim.get_world_pose() >>> position [0. 0. 0.] >>> orientation [1. 0. 0. 0.]
- initialize(physics_sim_view=None) None
Create a physics simulation view if not passed and using PhysX tensor API
Note
If the prim has been added to the world scene (e.g.,
world.scene.add(prim)), it will be automatically initialized when the world is reset (e.g.,world.reset()).- Parameters
physics_sim_view (omni.physics.tensors.SimulationView, optional) – current physics simulation view. Defaults to None.
Example:
>>> plane.initialize()
- is_valid() bool
Check if the prim path has a valid USD Prim at it
- Returns
True is the current prim path corresponds to a valid prim in stage. False otherwise.
- Return type
bool
Example:
>>> # given an existing and valid prim >>> plane.is_valid() True
- property name: Optional[str]
- Returns
name given to the prim when instantiating it. Otherwise None.
- Return type
str
Example:
>>> plane.name ground_plane
- post_reset() None
Reset the prim to its default state (position and orientation).
Example:
>>> plane.post_reset()
- property prim: pxr.Usd.Prim
- Returns
USD Prim object that this object holds.
- Return type
Usd.Prim
Example:
>>> plane.prim Usd.Prim(</World/GroundPlane>)
- property prim_path: str
- Returns
prim path in the stage.
- Return type
str
Example:
>>> plane.prim_path /World/GroundPlane
- set_default_state(position: Optional[Sequence[float]] = None, orientation: Optional[Sequence[float]] = None) None
Sets the default state of the prim (position and orientation), that will be used after each reset.
- Parameters
position (Optional[Sequence[float]], optional) – position in the world frame of the prim. shape is (3, ). Defaults to None, which means left unchanged.
orientation (Optional[Sequence[float]], optional) – quaternion orientation in the world frame of the prim. quaternion is scalar-first (w, x, y, z). shape is (4, ). Defaults to None, which means left unchanged.
Example:
>>> # configure default state >>> plane.set_default_state(position=np.array([0.0, 0.0, -1.0]), orientation=np.array([1, 0, 0, 0])) >>> >>> # set default states during post-reset >>> plane.post_reset()
- set_world_pose(position: Optional[Sequence[float]] = None, orientation: Optional[Sequence[float]] = None) None
Ses prim’s pose with respect to the world’s frame
Warning
This method will change (teleport) the prim pose immediately to the indicated value
- Parameters
position (Optional[Sequence[float]], optional) – position in the world frame of the prim. shape is (3, ). Defaults to None, which means left unchanged.
orientation (Optional[Sequence[float]], optional) – quaternion orientation in the world frame of the prim. quaternion is scalar-first (w, x, y, z). shape is (4, ). Defaults to None, which means left unchanged.
Hint
This method belongs to the methods used to set the prim state
Example:
>>> plane.set_world_pose(position=np.array([0.0, 0.0, 0.5]), orientation=np.array([1., 0., 0., 0.]))
- property xform_prim: omni.isaac.core.prims.xform_prim.XFormPrim
- Returns
wrapped object as a XFormPrim
- Return type
Example:
>>> plane.xform_prim <omni.isaac.core.prims.xform_prim.XFormPrim object at 0x7f1578d32560>
Visual Capsule
- class VisualCapsule(prim_path: str, name: str = 'visual_capsule', position: Optional[Sequence[float]] = None, translation: Optional[Sequence[float]] = None, orientation: Optional[Sequence[float]