Franka Robot [omni.isaac.franka]

Franka

class Franka(prim_path: str, name: str = 'franka_robot', usd_path: Optional[str] = None, position: Optional[numpy.ndarray] = None, orientation: Optional[numpy.ndarray] = None, end_effector_prim_name: Optional[str] = None, gripper_dof_names: Optional[List[str]] = None, gripper_open_position: Optional[numpy.ndarray] = None, gripper_closed_position: Optional[numpy.ndarray] = None, deltas: Optional[numpy.ndarray] = None)

[summary]

Parameters

prim_path (str) – [description]
name (str, optional) – [description]. Defaults to “franka_robot”.
usd_path (Optional[str], optional) – [description]. Defaults to None.
position (Optional[np.ndarray], optional) – [description]. Defaults to None.
orientation (Optional[np.ndarray], optional) – [description]. Defaults to None.
end_effector_prim_name (Optional[str], optional) – [description]. Defaults to None.
gripper_dof_names (Optional[List[str]], optional) – [description]. Defaults to None.
gripper_open_position (Optional[np.ndarray], optional) – [description]. Defaults to None.
gripper_closed_position (Optional[np.ndarray], optional) – [description]. Defaults to None.

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	`type`	DOF type: invalid/unknown/uninitialized (0), rotation (1), translation (2)
1	`hasLimits`	Whether the DOF has limits
2	`lower`	Lower DOF limit (in radians or meters)
3	`upper`	Upper DOF limit (in radians or meters)
4	`driveMode`	Drive mode for the DOF: force (1), acceleration (2)
5	`maxVelocity`	Maximum DOF velocity. In radians/s, or stage_units/s
6	`maxEffort`	Maximum DOF effort. In N or N*stage_units
7	`stiffness`	DOF stiffness
8	`damping`	DOF 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()

property end_effector: omni.isaac.core.prims.rigid_prim.RigidPrim

[summary]

Returns: [description]
Return type: RigidPrim

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: ArticulationAction

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_efforts method

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: VisualMaterial

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_controller was passed during class instantiation, a default controller of type ArticulationController (a Proportional-Derivative controller that can apply position targets, velocity targets and efforts) will be used

Returns: articulation controller
Return type: ArticulationController

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: XFormPrimState

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: JointsState

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: JointsState

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 gripper: omni.isaac.manipulators.grippers.parallel_gripper.ParallelGripper

[summary]

Returns: [description]
Return type: ParallelGripper

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=None) → None: [summary]

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: [summary]

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_efforts

Example:

>>> 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_efforts

Example:

>>> # 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_action method 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_efforts

Example:

>>> # 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_action method 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_efforts

Example:

>>> # 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() or world.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_efforts

Example:

>>> 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,).

Franka Kinematics Solver

class KinematicsSolver(robot_articulation: omni.isaac.core.articulations.articulation.Articulation, end_effector_frame_name: Optional[str] = None)

Kinematics Solver for Franka robot. This class loads a LulaKinematicsSovler object

Parameters

robot_articulation (Articulation) – An initialized Articulation object representing this Franka
end_effector_frame_name (Optional[str]) – The name of the Franka end effector. If None, an end effector link will be automatically selected. Defaults to None.

compute_end_effector_pose(position_only=False) → Tuple[numpy.array, numpy.array]

Compute the pose of the robot end effector using the simulated robot’s current joint positions

Parameters

position_only (bool) – If True, only the frame positions need to be calculated. The returned rotation may be left undefined.

Returns

position: Translation vector describing the translation of the robot end effector relative to the USD global frame (in stage units)

rotation: (3x3) rotation matrix describing the rotation of the frame relative to the USD stage global frame

Return type

Tuple[np.array,np.array]

compute_inverse_kinematics(target_position: numpy.array, target_orientation: Optional[numpy.array] = None, position_tolerance: Optional[float] = None, orientation_tolerance: Optional[float] = None) → Tuple[omni.isaac.core.utils.types.ArticulationAction, bool]

Compute inverse kinematics for the end effector frame using the current robot position as a warm start. The result is returned in an articulation action that can be directly applied to the robot.

Parameters

target_position (np.array) – target translation of the target frame (in stage units) relative to the USD stage origin
target_orientation (np.array) – target orientation of the target frame relative to the USD stage global frame. Defaults to None.
position_tolerance (float) – l-2 norm of acceptable position error (in stage units) between the target and achieved translations. Defaults to None.
tolerance (orientation) – magnitude of rotation (in radians) separating the target orientation from the achieved orienatation. orientation_tolerance is well defined for values between 0 and pi. Defaults to None.

Returns

ik_result: An ArticulationAction that can be applied to the robot to move the end effector frame to the desired position.

success: Solver converged successfully

Return type

Tuple[ArticulationAction, bool]

get_end_effector_frame() → str

Get the end effector frame

Returns: Name of the end effector frame
Return type: str

get_joints_subset() → omni.isaac.core.articulations.articulation_subset.ArticulationSubset

Returns: A wrapper class for querying USD robot joint states in the order expected by the kinematics solver
Return type: ArticulationSubset

get_kinematics_solver() → omni.isaac.motion_generation.kinematics_interface.KinematicsSolver

Get the underlying KinematicsSolver instance used by this class.

Returns: A class that can solve forward and inverse kinematics for a specified robot.
Return type: KinematicsSolver

set_end_effector_frame(end_effector_frame_name: str) → None

Set the name for the end effector frame. If the frame is not recognized by the internal KinematicsSolver instance, an error will be thrown

Parameters: end_effector_frame_name (str) – Name of the robot end effector frame.

Franka Controllers

class PickPlaceController(name: str, gripper: omni.isaac.manipulators.grippers.parallel_gripper.ParallelGripper, robot_articulation: omni.isaac.core.articulations.articulation.Articulation, end_effector_initial_height: Optional[float] = None, events_dt: Optional[List[float]] = None)

[summary]

Parameters

name (str) – [description]
gripper (ParallelGripper) – [description]
robot_articulation (Articulation) – [description]
end_effector_initial_height (Optional[float], optional) – [description]. Defaults to None.
events_dt (Optional[List[float]], optional) – [description]. Defaults to None.

forward(picking_position: numpy.ndarray, placing_position: numpy.ndarray, current_joint_positions: numpy.ndarray, end_effector_offset: Optional[numpy.ndarray] = None, end_effector_orientation: Optional[numpy.ndarray] = None) → omni.isaac.core.utils.types.ArticulationAction

Runs the controller one step.

Parameters

picking_position (np.ndarray) – The object’s position to be picked in local frame.
placing_position (np.ndarray) – The object’s position to be placed in local frame.
current_joint_positions (np.ndarray) – Current joint positions of the robot.
end_effector_offset (Optional[np.ndarray], optional) – offset of the end effector target. Defaults to None.
end_effector_orientation (Optional[np.ndarray], optional) – end effector orientation while picking and placing. Defaults to None.

Returns

action to be executed by the ArticulationController

Return type

ArticulationAction

get_current_event() → int

Returns: Current event/ phase of the state machine
Return type: int

is_done() → bool

Returns: True if the state machine reached the last phase. Otherwise False.
Return type: bool

is_paused() → bool

Returns: True if the state machine is paused. Otherwise False.
Return type: bool

pause() → None: Pauses the state machine’s time and phase.

reset(end_effector_initial_height: Optional[float] = None, events_dt: Optional[List[float]] = None) → None

Resets the state machine to start from the first phase/ event

Parameters

end_effector_initial_height (Optional[float], optional) – end effector initial picking height to start from. If not defined, set to 0.3 meters. Defaults to None.
events_dt (Optional[List[float]], optional) – Dt of each phase/ event step. 10 phases dt has to be defined. Defaults to None.

Raises

Exception – events dt need to be list or numpy array
Exception – events dt need have length of 10

resume() → None: Resumes the state machine’s time and phase.

class RMPFlowController(name: str, robot_articulation: omni.isaac.core.articulations.articulation.Articulation, physics_dt: float = 0.016666666666666666)

[summary]

Parameters

name (str) – [description]
robot_articulation (Articulation) – [description]
physics_dt (float, optional) – [description]. Defaults to 1.0/60.0.

add_obstacle(obstacle: <module 'omni.isaac.core.objects' from '/builds/omniverse/isaac/omni_isaac_sim/_build/linux-x86_64/debug/exts/omni.isaac.core/omni/isaac/core/objects/__init__.py'>, static: bool = False) → None

Add an object from omni.isaac.core.objects as an obstacle to the motion_policy

Parameters

obstacle (omni.isaac.core.objects) – Dynamic, Visual, or Fixed object from omni.isaac.core.objects
static (bool) – If True, the obstacle may be assumed by the MotionPolicy to remain stationary over time

forward(target_end_effector_position: numpy.ndarray, target_end_effector_orientation: Optional[numpy.ndarray] = None) → omni.isaac.core.utils.types.ArticulationAction

Compute an ArticulationAction representing the desired robot state for the next simulation frame

Parameters

target_translation (nd.array) – Translation vector (3x1) for robot end effector. Target translation should be specified in the same units as the USD stage, relative to the stage origin.
target_orientation (Optional[np.ndarray], optional) – Quaternion of desired rotation for robot end effector relative to USD stage global frame. Target orientation defaults to None, which means that the robot may reach the target with any orientation.

Returns

A wrapper object containing the desired next state for the robot

Return type

ArticulationAction

get_articulation_motion_policy() → omni.isaac.motion_generation.articulation_motion_policy.ArticulationMotionPolicy

Get ArticulationMotionPolicy that was passed to this class on initialization

Returns: a wrapper around a MotionPolicy for computing ArticulationActions that can be directly applied to the robot
Return type: ArticulationMotionPolicy

get_motion_policy() → omni.isaac.motion_generation.motion_policy_interface.MotionPolicy

Get MotionPolicy object that is being used to generate robot motions

Returns: An instance of a MotionPolicy that is being used to compute robot motions
Return type: MotionPolicy

remove_obstacle(obstacle: <module 'omni.isaac.core.objects' from '/builds/omniverse/isaac/omni_isaac_sim/_build/linux-x86_64/debug/exts/omni.isaac.core/omni/isaac/core/objects/__init__.py'>) → None

Remove and added obstacle from the motion_policy

Parameters: obstacle (omni.isaac.core.objects) – Object from omni.isaac.core.objects that has been added to the motion_policy

reset()

class StackingController(name: str, gripper: omni.isaac.manipulators.grippers.parallel_gripper.ParallelGripper, robot_articulation: omni.isaac.core.articulations.articulation.Articulation, picking_order_cube_names: List[str], robot_observation_name: str)

[summary]

Parameters

name (str) – [description]
gripper (ParallelGripper) – [description]
robot_prim_path (str) – [description]
picking_order_cube_names (List[str]) – [description]
robot_observation_name (str) – [description]

forward(observations: dict, end_effector_orientation: Optional[numpy.ndarray] = None, end_effector_offset: Optional[numpy.ndarray] = None) → omni.isaac.core.utils.types.ArticulationAction

A controller should take inputs and returns an ArticulationAction to be then passed to the: ArticulationController.

Parameters: observations (dict) – [description]
Raises: NotImplementedError – [description]
Returns: [description]
Return type: ArticulationAction

is_done() → bool

[summary]

Returns: [description]
Return type: bool

reset(picking_order_cube_names: Optional[List[str]] = None) → None

[summary]

Parameters: picking_order_cube_names (Optional[List[str]], optional) – [description]. Defaults to None.

Franka Tasks

class FollowTarget(name: str = 'franka_follow_target', target_prim_path: Optional[str] = None, target_name: Optional[str] = None, target_position: Optional[numpy.ndarray] = None, target_orientation: Optional[numpy.ndarray] = None, offset: Optional[numpy.ndarray] = None, franka_prim_path: Optional[str] = None, franka_robot_name: Optional[str] = None)

[summary]

Parameters

name (str, optional) – [description]. Defaults to “franka_follow_target”.
target_prim_path (Optional[str], optional) – [description]. Defaults to None.
target_name (Optional[str], optional) – [description]. Defaults to None.
target_position (Optional[np.ndarray], optional) – [description]. Defaults to None.
target_orientation (Optional[np.ndarray], optional) – [description]. Defaults to None.
offset (Optional[np.ndarray], optional) – [description]. Defaults to None.
franka_prim_path (Optional[str], optional) – [description]. Defaults to None.
franka_robot_name (Optional[str], optional) – [description]. Defaults to None.

add_obstacle(position: Optional[numpy.ndarray] = None)

[summary]

Parameters: position (np.ndarray, optional) – [description]. Defaults to np.array([0.1, 0.1, 1.0]).

calculate_metrics() → dict: [summary]

cleanup() → None: [summary]

property device

get_description() → str

[summary]

Returns: [description]
Return type: str

get_observations() → dict

[summary]

Returns: [description]
Return type: dict

get_obstacle_to_delete() → None

[summary]

Returns: [description]
Return type: [type]

get_params() → dict

[summary]

Returns: [description]
Return type: dict

get_task_objects() → dict

[summary]

Returns: [description]
Return type: dict

is_done() → bool: [summary]

property name: str

[summary]

Returns: [description]
Return type: str

obstacles_exist() → bool

[summary]

Returns: [description]
Return type: bool

post_reset() → None: [summary]

pre_step(time_step_index: int, simulation_time: float) → None

[summary]

Parameters

time_step_index (int) – [description]
simulation_time (float) – [description]

remove_obstacle(name: Optional[str] = None) → None

[summary]

Parameters: name (Optional[str], optional) – [description]. Defaults to None.

property scene: omni.isaac.core.scenes.scene.Scene

Scene of the world

Returns: [description]
Return type: Scene

set_params(target_prim_path: Optional[str] = None, target_name: Optional[str] = None, target_position: Optional[numpy.ndarray] = None, target_orientation: Optional[numpy.ndarray] = None) → None

[summary]

Parameters

target_prim_path (Optional[str], optional) – [description]. Defaults to None.
target_name (Optional[str], optional) – [description]. Defaults to None.
target_position (Optional[np.ndarray], optional) – [description]. Defaults to None.
target_orientation (Optional[np.ndarray], optional) – [description]. Defaults to None.

set_robot() → omni.isaac.franka.franka.Franka

[summary]

Returns: [description]
Return type: Franka

set_up_scene(scene: omni.isaac.core.scenes.scene.Scene) → None

[summary]

Parameters: scene (Scene) – [description]

target_reached() → bool

[summary]

Returns: [description]
Return type: bool

class PickPlace(name: str = 'franka_pick_place', cube_initial_position: Optional[numpy.ndarray] = None, cube_initial_orientation: Optional[numpy.ndarray] = None, target_position: Optional[numpy.ndarray] = None, cube_size: Optional[numpy.ndarray] = None, offset: Optional[numpy.ndarray] = None)

[summary]

Parameters

name (str, optional) – [description]. Defaults to “franka_pick_place”.
cube_initial_position (Optional[np.ndarray], optional) – [description]. Defaults to None.
cube_initial_orientation (Optional[np.ndarray], optional) – [description]. Defaults to None.
target_position (Optional[np.ndarray], optional) – [description]. Defaults to None.
cube_size (Optional[np.ndarray], optional) – [description]. Defaults to None.
offset (Optional[np.ndarray], optional) – [description]. Defaults to None.

calculate_metrics() → dict: [summary]

cleanup() → None: Called before calling a reset() on the world to removed temporary objects that were added during simulation for instance.

property device

get_description() → str

[summary]

Returns: [description]
Return type: str

get_observations() → dict

[summary]

Returns: [description]
Return type: dict

get_params() → dict

Gets the parameters of the task.: This is defined differently for each task in order to access the task’s objects and values. Note that this is different from get_observations. Things like the robot name, block name..etc can be defined here for faster retrieval. should have the form of params_representation[“param_name”] = {“value”: param_value, “modifiable”: bool}

Raises: NotImplementedError – [description]
Returns: defined parameters of the task.
Return type: dict

get_task_objects() → dict

[summary]

Returns: [description]
Return type: dict

is_done() → bool: [summary]

property name: str

[summary]

Returns: [description]
Return type: str

post_reset() → None: Calls while doing a .reset() on the world.

pre_step(time_step_index: int, simulation_time: float) → None

[summary]

Parameters

time_step_index (int) – [description]
simulation_time (float) – [description]

property scene: omni.isaac.core.scenes.scene.Scene

Scene of the world

Returns: [description]
Return type: Scene

set_params(cube_position: Optional[numpy.ndarray] = None, cube_orientation: Optional[numpy.ndarray] = None, target_position: Optional[numpy.ndarray] = None) → None

Changes the modifiable parameters of the task

Raises: NotImplementedError – [description]

set_robot() → omni.isaac.franka.franka.Franka

[summary]

Returns: [description]
Return type: Franka

set_up_scene(scene: omni.isaac.core.scenes.scene.Scene) → None

[summary]

Parameters: scene (Scene) – [description]

class Stacking(name: str = 'franka_stacking', target_position: Optional[numpy.ndarray] = None, cube_size: Optional[numpy.ndarray] = None, offset: Optional[numpy.ndarray] = None)

[summary]

Parameters

name (str, optional) – [description]. Defaults to “franka_stacking”.
target_position (Optional[np.ndarray], optional) – [description]. Defaults to None.
cube_size (Optional[np.ndarray], optional) – [description]. Defaults to None.
offset (Optional[np.ndarray], optional) – [description]. Defaults to None.

calculate_metrics() → dict

[summary]

Raises: NotImplementedError – [description]
Returns: [description]
Return type: dict

cleanup() → None: Called before calling a reset() on the world to removed temporary objects that were added during simulation for instance.

property device

get_cube_names() → List[str]

[summary]

Returns: [description]
Return type: List[str]

get_description() → str

[summary]

Returns: [description]
Return type: str

get_observations() → dict

[summary]

Returns: [description]
Return type: dict

get_params() → dict

[summary]

Returns: [description]
Return type: dict

get_task_objects() → dict

[summary]

Returns: [description]
Return type: dict

is_done() → bool

[summary]

Raises: NotImplementedError – [description]
Returns: [description]
Return type: bool

property name: str

[summary]

Returns: [description]
Return type: str

post_reset() → None: [summary]

pre_step(time_step_index: int, simulation_time: float) → None

[summary]

Parameters

time_step_index (int) – [description]
simulation_time (float) – [description]

property scene: omni.isaac.core.scenes.scene.Scene

Scene of the world

Returns: [description]
Return type: Scene

set_params(cube_name: Optional[str] = None, cube_position: Optional[str] = None, cube_orientation: Optional[str] = None, stack_target_position: Optional[str] = None) → None

[summary]

Parameters

cube_name (Optional[str], optional) – [description]. Defaults to None.
cube_position (Optional[str], optional) – [description]. Defaults to None.
cube_orientation (Optional[str], optional) – [description]. Defaults to None.
stack_target_position (Optional[str], optional) – [description]. Defaults to None.

set_robot() → omni.isaac.franka.franka.Franka

[summary]

Returns: [description]
Return type: Franka

set_up_scene(scene: omni.isaac.core.scenes.scene.Scene) → None

[summary]

Parameters: scene (Scene) – [description]