Prevents import of pink when running other workflows (#317)

This change prevents importing pink/dex-retargeting when using other
IsaacLab scripts.

* Change the import structure to only import ``pinocchio`` when
``pink-ik`` or ``dex-retargeting`` is being used.
* This also solves for the problem that ``pink-ik`` and
``dex-retargeting`` are not supported in windows.
* Removed ``isaacsim.robot_motion.lula`` and
``isaacsim.robot_motion.motion_generation`` from the default loaded
Isaac Sim extensions and enable them only for RMPFlow
* Moved pink ik action config to a separate file.
* The pick_place task is now blacklisted from being imported
automatically by isaaclab_tasks and have to be imported
  manually by the script.

- Bug fix (non-breaking change which fixes an issue)
- This change requires a documentation update

- [x] I have run the [`pre-commit` checks](https://pre-commit.com/) with
`./isaaclab.sh --format`
- [x] I have made corresponding changes to the documentation
- [x] My changes generate no new warnings
- [x] I have updated the changelog and the corresponding version in the
extension's `config/extension.toml` file
- [x] I have added my name to the `CONTRIBUTORS.md` or my name already
exists there

---------
Signed-off-by: Kelly Guo <kellyguo123@hotmail.com>
Co-authored-by: chengronglai <chengrongl@nvidia.com>
Co-authored-by: Kelly Guo <kellyg@nvidia.com>

apps/isaaclab.python.kit

@@ -24,8 +24,6 @@ keywords = ["experience", "app", "usd"]
 "isaacsim.gui.menu" = {}
 "isaacsim.gui.property" = {}
 "isaacsim.replicator.behavior" = {}
-"isaacsim.robot_motion.lula" = {}
-"isaacsim.robot_motion.motion_generation" = {}
 "isaacsim.robot.manipulators" = {}
 "isaacsim.robot.policy.examples" = {}
 "isaacsim.robot.schema" = {}

docs/source/overview/teleop_imitation.rst

@@ -325,7 +325,7 @@ Collect a set of human demonstrations using the command below. We recommend 10 s
    --task Isaac-PickPlace-GR1T2-Abs-v0 \
    --teleop_device dualhandtracking_abs \
    --dataset_file ./datasets/dataset_gr1.hdf5 \
-   --num_demos 10
+   --num_demos 10 --enable_pinocchio
 
 Unlike the prior Franka stacking task, the GR-1 pick and place task uses manual annotation to define subtasks.
 Each demo requires a single annotation which denotes when the right robot arm finishes the "idle" subtask and begins to
@@ -337,7 +337,7 @@ move towards the target object. Annotate the demonstrations by running the follo
    --device cuda \
    --task Isaac-PickPlace-GR1T2-Abs-Mimic-v0 \
    --input_file ./datasets/dataset_gr1.hdf5 \
-   --output_file ./datasets/dataset_annotated_gr1.hdf5
+   --output_file ./datasets/dataset_annotated_gr1.hdf5 --enable_pinocchio
 
 .. note::
 
@@ -366,7 +366,7 @@ Place the file under ``IsaacLab/datasets`` and run the following command to gene
 .. code:: bash
 
    ./isaaclab.sh -p scripts/imitation_learning/isaaclab_mimic/generate_dataset.py \
-   --device cuda --headless --num_envs 10 --generation_num_trials 1000 \
+   --device cuda --headless --num_envs 10 --generation_num_trials 1000 --enable_pinocchio \
    --input_file ./datasets/dataset_annotated_gr1.hdf5 --output_file ./datasets/generated_dataset_gr1.hdf5
 
 Train a policy
@@ -397,6 +397,7 @@ Visualize the results of the trained policy by running the following command, us
 
    ./isaaclab.sh -p scripts/imitation_learning/robomimic/play.py \
    --device cuda \
+   --enable_pinocchio \
    --task Isaac-PickPlace-GR1T2-Abs-v0 \
    --num_rollouts 50 \
    --norm_factor_min <NORM_FACTOR_MIN> \

scripts/imitation_learning/isaaclab_mimic/annotate_demos.py

@@ -9,10 +9,6 @@ Script to add mimic annotations to demos to be used as source demos for mimic da
 
 import argparse
 
-# Import pinocchio in the main script to force the use of the dependencies installed by IsaacLab and not the one installed by Isaac Sim
-# pinocchio is required by the Pink IK controller
-import pinocchio  # noqa: F401
-
 from isaaclab.app import AppLauncher
 
 # Launching Isaac Sim Simulator first.
@@ -31,12 +27,23 @@ parser.add_argument(
     help="File name of the annotated output dataset file.",
 )
 parser.add_argument("--auto", action="store_true", default=False, help="Automatically annotate subtasks.")
+parser.add_argument(
+    "--enable_pinocchio",
+    action="store_true",
+    default=False,
+    help="Enable Pinocchio.",
+)
 
 # append AppLauncher cli args
 AppLauncher.add_app_launcher_args(parser)
 # parse the arguments
 args_cli = parser.parse_args()
 
+if args_cli.enable_pinocchio:
+    # Import pinocchio before AppLauncher to force the use of the version installed by IsaacLab and not the one installed by Isaac Sim
+    # pinocchio is required by the Pink IK controllers and the GR1T2 retargeter
+    import pinocchio  # noqa: F401
+
 # launch the simulator
 app_launcher = AppLauncher(args_cli)
 simulation_app = app_launcher.app
@@ -61,6 +68,9 @@ from isaaclab.utils import configclass
 from isaaclab.utils.datasets import EpisodeData, HDF5DatasetFileHandler
 
 import isaaclab_tasks  # noqa: F401
+
+if args_cli.enable_pinocchio:
+    import isaaclab_tasks.manager_based.manipulation.pick_place  # noqa: F401
 from isaaclab_tasks.utils.parse_cfg import parse_env_cfg
 
 is_paused = False

scripts/imitation_learning/isaaclab_mimic/generate_dataset.py

@@ -7,9 +7,6 @@
 Main data generation script.
 """
 
-# Import pinocchio in the main script to force the use of the dependencies installed by IsaacLab and not the one installed by Isaac Sim
-# pinocchio is required by the Pink IK controller
-import pinocchio  # noqa: F401
 
 """Launch Isaac Sim Simulator first."""
 
@@ -36,11 +33,22 @@ parser.add_argument(
     action="store_true",
     help="pause after every subtask during generation for debugging - only useful with render flag",
 )
+parser.add_argument(
+    "--enable_pinocchio",
+    action="store_true",
+    default=False,
+    help="Enable Pinocchio.",
+)
 # append AppLauncher cli args
 AppLauncher.add_app_launcher_args(parser)
 # parse the arguments
 args_cli = parser.parse_args()
 
+if args_cli.enable_pinocchio:
+    # Import pinocchio before AppLauncher to force the use of the version installed by IsaacLab and not the one installed by Isaac Sim
+    # pinocchio is required by the Pink IK controllers and the GR1T2 retargeter
+    import pinocchio  # noqa: F401
+
 # launch the simulator
 app_launcher = AppLauncher(args_cli)
 simulation_app = app_launcher.app

scripts/imitation_learning/robomimic/play.py

@@ -22,10 +22,6 @@ Args:
 
 import argparse
 
-# Import pinocchio in the main script to force the use of the dependencies installed by IsaacLab and not the one installed by Isaac Sim
-# pinocchio is required by the Pink IK controller
-import pinocchio  # noqa: F401
-
 from isaaclab.app import AppLauncher
 
 # add argparse arguments
@@ -44,6 +40,7 @@ parser.add_argument(
 parser.add_argument(
     "--norm_factor_max", type=float, default=None, help="Optional: maximum value of the normalization factor."
 )
+parser.add_argument("--enable_pinocchio", default=False, action="store_true", help="Enable Pinocchio.")
 
 
 # append AppLauncher cli args
@@ -51,6 +48,11 @@ AppLauncher.add_app_launcher_args(parser)
 # parse the arguments
 args_cli = parser.parse_args()
 
+if args_cli.enable_pinocchio:
+    # Import pinocchio before AppLauncher to force the use of the version installed by IsaacLab and not the one installed by Isaac Sim
+    # pinocchio is required by the Pink IK controllers and the GR1T2 retargeter
+    import pinocchio  # noqa: F401
+
 # launch omniverse app
 app_launcher = AppLauncher(args_cli)
 simulation_app = app_launcher.app

scripts/tools/record_demos.py

@@ -38,10 +38,6 @@ import torch
 # Omniverse logger
 import omni.log
 
-# Import pinocchio in the main script to force the use of the dependencies installed by IsaacLab and not the one installed by Isaac Sim
-# pinocchio is required by the Pink IK controller
-import pinocchio  # noqa: F401
-
 # Isaac Lab AppLauncher
 from isaaclab.app import AppLauncher
 
@@ -62,6 +58,12 @@ parser.add_argument(
     default=10,
     help="Number of continuous steps with task success for concluding a demo as successful. Default is 10.",
 )
+parser.add_argument(
+    "--enable_pinocchio",
+    action="store_true",
+    default=False,
+    help="Enable Pinocchio.",
+)
 
 # append AppLauncher cli args
 AppLauncher.add_app_launcher_args(parser)
@@ -69,6 +71,11 @@ AppLauncher.add_app_launcher_args(parser)
 args_cli = parser.parse_args()
 
 app_launcher_args = vars(args_cli)
+
+if args_cli.enable_pinocchio:
+    # Import pinocchio before AppLauncher to force the use of the version installed by IsaacLab and not the one installed by Isaac Sim
+    # pinocchio is required by the Pink IK controllers and the GR1T2 retargeter
+    import pinocchio  # noqa: F401
 if "handtracking" in args_cli.teleop_device.lower():
     app_launcher_args["xr"] = True
 
@@ -81,7 +88,10 @@ if "handtracking" in args_cli.teleop_device.lower():
 
 # Additional Isaac Lab imports that can only be imported after the simulator is running
 from isaaclab.devices import OpenXRDevice, Se3Keyboard, Se3SpaceMouse
-from isaaclab.devices.openxr.retargeters.humanoid.fourier.gr1t2_retargeter import GR1T2Retargeter
+
+if args_cli.enable_pinocchio:
+    from isaaclab.devices.openxr.retargeters.humanoid.fourier.gr1t2_retargeter import GR1T2Retargeter
+    import isaaclab_tasks.manager_based.manipulation.pick_place  # noqa: F401
 from isaaclab.devices.openxr.retargeters.manipulator import GripperRetargeter, Se3AbsRetargeter, Se3RelRetargeter
 from isaaclab.envs.mdp.recorders.recorders_cfg import ActionStateRecorderManagerCfg
 

scripts/tools/replay_demos.py

@@ -10,10 +10,6 @@
 
 import argparse
 
-# Import pinocchio in the main script to force the use of the dependencies installed by IsaacLab and not the one installed by Isaac Sim
-# pinocchio is required by the Pink IK controller
-import pinocchio  # noqa: F401
-
 from isaaclab.app import AppLauncher
 
 # add argparse arguments
@@ -37,6 +33,12 @@ parser.add_argument(
         " --num_envs is 1."
     ),
 )
+parser.add_argument(
+    "--enable_pinocchio",
+    action="store_true",
+    default=False,
+    help="Enable Pinocchio.",
+)
 
 # append AppLauncher cli args
 AppLauncher.add_app_launcher_args(parser)
@@ -44,6 +46,11 @@ AppLauncher.add_app_launcher_args(parser)
 args_cli = parser.parse_args()
 # args_cli.headless = True
 
+if args_cli.enable_pinocchio:
+    # Import pinocchio before AppLauncher to force the use of the version installed by IsaacLab and not the one installed by Isaac Sim
+    # pinocchio is required by the Pink IK controllers and the GR1T2 retargeter
+    import pinocchio  # noqa: F401
+
 # launch the simulator
 app_launcher = AppLauncher(args_cli)
 simulation_app = app_launcher.app

source/isaaclab/config/extension.toml

 [package]
 
 # Note: Semantic Versioning is used: https://semver.org/
-version = "0.36.10"
+version = "0.36.11"
 
 # Description
 title = "Isaac Lab framework for Robot Learning"

source/isaaclab/docs/CHANGELOG.rst

 Changelog
 ---------
 
-0.36.10 (2025-04-09)
+0.36.11 (2025-04-09)
 ~~~~~~~~~~~~~~~~~~~~
 
 Changed
@@ -12,8 +12,8 @@ Changed
   the cuda device, which results in NCCL errors on distributed setups.
 
 
-0.36.9 (2025-04-01)
-~~~~~~~~~~~~~~~~~~~
+0.36.10 (2025-04-01)
+~~~~~~~~~~~~~~~~~~~~
 
 Fixed
 ^^^^^
@@ -21,7 +21,7 @@ Fixed
 * Added check in RecorderManager to ensure that the success indicator is only set if the termination manager is present.
 
 
-0.36.8 (2025-03-24)
+0.36.9 (2025-03-24)
 ~~~~~~~~~~~~~~~~~~~
 
 Changed
@@ -31,7 +31,7 @@ Changed
   the default settings will be used from the experience files and the double definition is removed.
 
 
-0.36.7 (2025-03-17)
+0.36.8 (2025-03-17)
 ~~~~~~~~~~~~~~~~~~~
 
 Fixed
@@ -41,6 +41,18 @@ Fixed
   :attr:`effort_limit` is set.
 
 
+0.36.7 (2025-03-14)
+~~~~~~~~~~~~~~~~~~~
+
+Fixed
+^^^^^
+
+* Changed the import structure to only import ``pinocchio`` when ``pink-ik`` or ``dex-retargeting`` is being used.
+  This also solves for the problem that ``pink-ik`` and ``dex-retargeting`` are not supported in windows.
+* Removed ``isaacsim.robot_motion.lula`` and ``isaacsim.robot_motion.motion_generation`` from the default loaded Isaac Sim extensions.
+* Moved pink ik action config to a separate file.
+
+
 0.36.6 (2025-03-13)
 ~~~~~~~~~~~~~~~~~~~
 

source/isaaclab/isaaclab/controllers/__init__.py

@@ -15,5 +15,3 @@ from .differential_ik import DifferentialIKController
 from .differential_ik_cfg import DifferentialIKControllerCfg
 from .operational_space import OperationalSpaceController
 from .operational_space_cfg import OperationalSpaceControllerCfg
-from .pink_ik import PinkIKController
-from .pink_ik_cfg import PinkIKControllerCfg

source/isaaclab/isaaclab/controllers/rmp_flow.py

@@ -8,7 +8,14 @@ from dataclasses import MISSING
 
 import isaacsim.core.utils.prims as prim_utils
 from isaacsim.core.api.simulation_context import SimulationContext
-from isaacsim.core.prims.articulations import Articulation
+from isaacsim.core.prims import SingleArticulation
+
+# enable motion generation extensions
+from isaacsim.core.utils.extensions import enable_extension
+
+enable_extension("isaacsim.robot_motion.lula")
+enable_extension("isaacsim.robot_motion.motion_generation")
+
 from isaacsim.robot_motion.motion_generation import ArticulationMotionPolicy
 from isaacsim.robot_motion.motion_generation.lula.motion_policies import RmpFlow, RmpFlowSmoothed
 
@@ -86,7 +93,7 @@ class RmpFlowController:
         self.articulation_policies = list()
         for prim_path in self._prim_paths:
             # add robot reference
-            robot = Articulation(prim_path)
+            robot = SingleArticulation(prim_path)
             robot.initialize()
             # add controller
             rmpflow = controller_cls(

source/isaaclab/isaaclab/devices/openxr/retargeters/__init__.py

@@ -4,7 +4,6 @@
 # SPDX-License-Identifier: BSD-3-Clause
 """Retargeters for mapping input device data to robot commands."""
 
-from .humanoid.fourier.gr1t2_retargeter import GR1T2Retargeter
 from .manipulator.gripper_retargeter import GripperRetargeter
 from .manipulator.se3_abs_retargeter import Se3AbsRetargeter
 from .manipulator.se3_rel_retargeter import Se3RelRetargeter

source/isaaclab/isaaclab/envs/mdp/actions/actions_cfg.py

@@ -5,7 +5,7 @@
 
 from dataclasses import MISSING
 
-from isaaclab.controllers import DifferentialIKControllerCfg, OperationalSpaceControllerCfg, PinkIKControllerCfg
+from isaaclab.controllers import DifferentialIKControllerCfg, OperationalSpaceControllerCfg
 from isaaclab.managers.action_manager import ActionTerm, ActionTermCfg
 from isaaclab.utils import configclass
 
@@ -250,30 +250,6 @@ class DifferentialInverseKinematicsActionCfg(ActionTermCfg):
     """The configuration for the differential IK controller."""
 
 
-@configclass
-class PinkInverseKinematicsActionCfg(ActionTermCfg):
-    """Configuration for Pink inverse kinematics action term.
-
-    This configuration is used to define settings for the Pink inverse kinematics action term,
-    which is a inverse kinematics framework.
-    """
-
-    class_type: type[ActionTerm] = task_space_actions.PinkInverseKinematicsAction
-    """Specifies the action term class type for Pink inverse kinematics action."""
-
-    pink_controlled_joint_names: list[str] = MISSING
-    """List of joint names or regular expression patterns that specify the joints controlled by pink IK."""
-
-    ik_urdf_fixed_joint_names: list[str] = MISSING
-    """List of joint names that specify the joints to be locked in URDF."""
-
-    hand_joint_names: list[str] = MISSING
-    """List of joint names or regular expression patterns that specify the joints controlled by hand retargeting."""
-
-    controller: PinkIKControllerCfg = MISSING
-    """Configuration for the Pink IK controller that will be used to solve the inverse kinematics."""
-
-
 @configclass
 class OperationalSpaceControllerActionCfg(ActionTermCfg):
     """Configuration for operational space controller action term.

source/isaaclab/isaaclab/envs/mdp/actions/pink_actions_cfg.py

+# Copyright (c) 2025, The Isaac Lab Project Developers.
+# All rights reserved.
+#
+# SPDX-License-Identifier: BSD-3-Clause
+
+from dataclasses import MISSING
+
+from isaaclab.controllers.pink_ik_cfg import PinkIKControllerCfg
+from isaaclab.managers.action_manager import ActionTerm, ActionTermCfg
+from isaaclab.utils import configclass
+
+from . import pink_task_space_actions
+
+
+@configclass
+class PinkInverseKinematicsActionCfg(ActionTermCfg):
+    """Configuration for Pink inverse kinematics action term.
+
+    This configuration is used to define settings for the Pink inverse kinematics action term,
+    which is a inverse kinematics framework.
+    """
+
+    class_type: type[ActionTerm] = pink_task_space_actions.PinkInverseKinematicsAction
+    """Specifies the action term class type for Pink inverse kinematics action."""
+
+    pink_controlled_joint_names: list[str] = MISSING
+    """List of joint names or regular expression patterns that specify the joints controlled by pink IK."""
+
+    ik_urdf_fixed_joint_names: list[str] = MISSING
+    """List of joint names that specify the joints to be locked in URDF."""
+
+    hand_joint_names: list[str] = MISSING
+    """List of joint names or regular expression patterns that specify the joints controlled by hand retargeting."""
+
+    controller: PinkIKControllerCfg = MISSING
+    """Configuration for the Pink IK controller that will be used to solve the inverse kinematics."""

source/isaaclab/isaaclab/envs/mdp/actions/pink_task_space_actions.py

+# Copyright (c) 2025, The Isaac Lab Project Developers.
+# All rights reserved.
+#
+# SPDX-License-Identifier: BSD-3-Clause
+
+from __future__ import annotations
+
+import copy
+import torch
+from collections.abc import Sequence
+from typing import TYPE_CHECKING
+
+import isaaclab.utils.math as math_utils
+from isaaclab.assets.articulation import Articulation
+from isaaclab.controllers.pink_ik import PinkIKController
+from isaaclab.managers.action_manager import ActionTerm
+
+if TYPE_CHECKING:
+    from isaaclab.envs import ManagerBasedEnv
+
+    from . import pink_actions_cfg
+
+
+class PinkInverseKinematicsAction(ActionTerm):
+    r"""Pink Inverse Kinematics action term.
+
+    This action term processes the action tensor and sets these setpoints in the pink IK framework
+    The action tensor is ordered in the order of the tasks defined in PinkIKControllerCfg
+    """
+
+    cfg: pink_actions_cfg.PinkInverseKinematicsActionCfg
+    """Configuration for the Pink Inverse Kinematics action term."""
+
+    _asset: Articulation
+    """The articulation asset to which the action term is applied."""
+
+    def __init__(self, cfg: pink_actions_cfg.PinkInverseKinematicsActionCfg, env: ManagerBasedEnv):
+        """Initialize the Pink Inverse Kinematics action term.
+
+        Args:
+            cfg: The configuration for this action term.
+            env: The environment in which the action term will be applied.
+        """
+        super().__init__(cfg, env)
+
+        # Resolve joint IDs and names based on the configuration
+        self._pink_controlled_joint_ids, self._pink_controlled_joint_names = self._asset.find_joints(
+            self.cfg.pink_controlled_joint_names
+        )
+        self.cfg.controller.joint_names = self._pink_controlled_joint_names
+        self._hand_joint_ids, self._hand_joint_names = self._asset.find_joints(self.cfg.hand_joint_names)
+        self._joint_ids = self._pink_controlled_joint_ids + self._hand_joint_ids
+        self._joint_names = self._pink_controlled_joint_names + self._hand_joint_names
+
+        # Initialize the Pink IK controller
+        assert env.num_envs > 0, "Number of environments specified are less than 1."
+        self._ik_controllers = []
+        for _ in range(env.num_envs):
+            self._ik_controllers.append(PinkIKController(cfg=copy.deepcopy(self.cfg.controller), device=self.device))
+
+        # Create tensors to store raw and processed actions
+        self._raw_actions = torch.zeros(self.num_envs, self.action_dim, device=self.device)
+        self._processed_actions = torch.zeros_like(self.raw_actions)
+
+        # Get the simulation time step
+        self._sim_dt = env.sim.get_physics_dt()
+
+        self.total_time = 0  # Variable to accumulate the total time
+        self.num_runs = 0  # Counter for the number of runs
+
+        # Save the base_link_frame pose in the world frame as a transformation matrix in
+        # order to transform the desired pose of the controlled_frame to be with respect to the base_link_frame
+        # Shape of env.scene[self.cfg.articulation_name].data.body_link_state_w is (num_instances, num_bodies, 13)
+        base_link_frame_in_world_origin = env.scene[self.cfg.controller.articulation_name].data.body_link_state_w[
+            :,
+            env.scene[self.cfg.controller.articulation_name].data.body_names.index(self.cfg.controller.base_link_name),
+            :7,
+        ]
+
+        # Get robot base link frame in env origin frame
+        base_link_frame_in_env_origin = copy.deepcopy(base_link_frame_in_world_origin)
+        base_link_frame_in_env_origin[:, :3] -= self._env.scene.env_origins
+
+        self.base_link_frame_in_env_origin = math_utils.make_pose(
+            base_link_frame_in_env_origin[:, :3], math_utils.matrix_from_quat(base_link_frame_in_env_origin[:, 3:7])
+        )
+
+    # """
+    # Properties.
+    # """
+
+    @property
+    def hand_joint_dim(self) -> int:
+        """Dimension for hand joint positions."""
+        return self.cfg.controller.num_hand_joints
+
+    @property
+    def position_dim(self) -> int:
+        """Dimension for position (x, y, z)."""
+        return 3
+
+    @property
+    def orientation_dim(self) -> int:
+        """Dimension for orientation (w, x, y, z)."""
+        return 4
+
+    @property
+    def pose_dim(self) -> int:
+        """Total pose dimension (position + orientation)."""
+        return self.position_dim + self.orientation_dim
+
+    @property
+    def action_dim(self) -> int:
+        """Dimension of the action space (based on number of tasks and pose dimension)."""
+        # The tasks for all the controllers are the same, hence just using the first one to calculate the action_dim
+        return len(self._ik_controllers[0].cfg.variable_input_tasks) * self.pose_dim + self.hand_joint_dim
+
+    @property
+    def raw_actions(self) -> torch.Tensor:
+        """Get the raw actions tensor."""
+        return self._raw_actions
+
+    @property
+    def processed_actions(self) -> torch.Tensor:
+        """Get the processed actions tensor."""
+        return self._processed_actions
+
+    # """
+    # Operations.
+    # """
+
+    def process_actions(self, actions: torch.Tensor):
+        """Process the input actions and set targets for each task.
+
+        Args:
+            actions: The input actions tensor.
+        """
+        # Store the raw actions
+        self._raw_actions[:] = actions
+        self._processed_actions[:] = self.raw_actions
+
+        # Make a copy of actions before modifying so that raw actions are not modified
+        actions_clone = actions.clone()
+
+        # Extract hand joint positions (last 22 values)
+        self._target_hand_joint_positions = actions_clone[:, -self.hand_joint_dim :]
+
+        # The action tensor provides the desired pose of the controlled_frame with respect to the env origin frame
+        # But the pink IK controller expects the desired pose of the controlled_frame with respect to the base_link_frame
+        # So we need to transform the desired pose of the controlled_frame to be with respect to the base_link_frame
+
+        # Get the controlled_frame pose wrt to the env origin frame
+        all_controlled_frames_in_env_origin = []
+        # The contrllers for all envs are the same, hence just using the first one to get the number of variable_input_tasks
+        for task_index in range(len(self._ik_controllers[0].cfg.variable_input_tasks)):
+            controlled_frame_in_env_origin_pos = actions_clone[
+                :, task_index * self.pose_dim : task_index * self.pose_dim + self.position_dim
+            ]
+            controlled_frame_in_env_origin_quat = actions_clone[
+                :, task_index * self.pose_dim + self.position_dim : (task_index + 1) * self.pose_dim
+            ]
+            controlled_frame_in_env_origin = math_utils.make_pose(
+                controlled_frame_in_env_origin_pos, math_utils.matrix_from_quat(controlled_frame_in_env_origin_quat)
+            )
+            all_controlled_frames_in_env_origin.append(controlled_frame_in_env_origin)
+        # Stack all the controlled_frame poses in the env origin frame. Shape is (num_tasks, num_envs , 4, 4)
+        all_controlled_frames_in_env_origin = torch.stack(all_controlled_frames_in_env_origin)
+
+        # Transform the controlled_frame to be with respect to the base_link_frame using batched matrix multiplication
+        controlled_frame_in_base_link_frame = math_utils.pose_in_A_to_pose_in_B(
+            all_controlled_frames_in_env_origin, math_utils.pose_inv(self.base_link_frame_in_env_origin)
+        )
+
+        controlled_frame_in_base_link_frame_pos, controlled_frame_in_base_link_frame_mat = math_utils.unmake_pose(
+            controlled_frame_in_base_link_frame
+        )
+
+        # Loop through each task and set the target
+        for env_index, ik_controller in enumerate(self._ik_controllers):
+            for task_index, task in enumerate(ik_controller.cfg.variable_input_tasks):
+                target = task.transform_target_to_world
+                target.translation = controlled_frame_in_base_link_frame_pos[task_index, env_index, :].cpu().numpy()
+                target.rotation = controlled_frame_in_base_link_frame_mat[task_index, env_index, :].cpu().numpy()
+                task.set_target(target)
+
+    def apply_actions(self):
+        # start_time = time.time()  # Capture the time before the step
+        """Apply the computed joint positions based on the inverse kinematics solution."""
+        all_envs_joint_pos_des = []
+        for env_index, ik_controller in enumerate(self._ik_controllers):
+            curr_joint_pos = self._asset.data.joint_pos[:, self._pink_controlled_joint_ids].cpu().numpy()[env_index]
+            joint_pos_des = ik_controller.compute(curr_joint_pos, self._sim_dt)
+            all_envs_joint_pos_des.append(joint_pos_des)
+        all_envs_joint_pos_des = torch.stack(all_envs_joint_pos_des)
+        # Combine IK joint positions with hand joint positions
+        all_envs_joint_pos_des = torch.cat((all_envs_joint_pos_des, self._target_hand_joint_positions), dim=1)
+
+        self._asset.set_joint_position_target(all_envs_joint_pos_des, self._joint_ids)
+
+    def reset(self, env_ids: Sequence[int] | None = None) -> None:
+        """Reset the action term for specified environments.
+
+        Args:
+            env_ids: A list of environment IDs to reset. If None, all environments are reset.
+        """
+        self._raw_actions[env_ids] = torch.zeros(self.action_dim, device=self.device)

source/isaaclab/isaaclab/envs/mdp/actions/task_space_actions.py

@@ -5,7 +5,6 @@
 
 from __future__ import annotations
 
-import copy
 import torch
 from collections.abc import Sequence
 from typing import TYPE_CHECKING
@@ -18,7 +17,6 @@ import isaaclab.utils.string as string_utils
 from isaaclab.assets.articulation import Articulation
 from isaaclab.controllers.differential_ik import DifferentialIKController
 from isaaclab.controllers.operational_space import OperationalSpaceController
-from isaaclab.controllers.pink_ik import PinkIKController
 from isaaclab.managers.action_manager import ActionTerm
 from isaaclab.sensors import ContactSensor, ContactSensorCfg, FrameTransformer, FrameTransformerCfg
 from isaaclab.sim.utils import find_matching_prims
@@ -29,191 +27,6 @@ if TYPE_CHECKING:
     from . import actions_cfg
 
 
-class PinkInverseKinematicsAction(ActionTerm):
-    r"""Pink Inverse Kinematics action term.
-
-    This action term processes the action tensor and sets these setpoints in the pink IK framework
-    The action tensor is ordered in the order of the tasks defined in PinkIKControllerCfg
-    """
-
-    cfg: actions_cfg.PinkInverseKinematicsActionCfg
-    """Configuration for the Pink Inverse Kinematics action term."""
-
-    _asset: Articulation
-    """The articulation asset to which the action term is applied."""
-
-    def __init__(self, cfg: actions_cfg.PinkInverseKinematicsActionCfg, env: ManagerBasedEnv):
-        """Initialize the Pink Inverse Kinematics action term.
-
-        Args:
-            cfg: The configuration for this action term.
-            env: The environment in which the action term will be applied.
-        """
-        super().__init__(cfg, env)
-
-        # Resolve joint IDs and names based on the configuration
-        self._pink_controlled_joint_ids, self._pink_controlled_joint_names = self._asset.find_joints(
-            self.cfg.pink_controlled_joint_names
-        )
-        self.cfg.controller.joint_names = self._pink_controlled_joint_names
-        self._hand_joint_ids, self._hand_joint_names = self._asset.find_joints(self.cfg.hand_joint_names)
-        self._joint_ids = self._pink_controlled_joint_ids + self._hand_joint_ids
-        self._joint_names = self._pink_controlled_joint_names + self._hand_joint_names
-
-        # Initialize the Pink IK controller
-        assert env.num_envs > 0, "Number of environments specified are less than 1."
-        self._ik_controllers = []
-        for _ in range(env.num_envs):
-            self._ik_controllers.append(PinkIKController(cfg=copy.deepcopy(self.cfg.controller), device=self.device))
-
-        # Create tensors to store raw and processed actions
-        self._raw_actions = torch.zeros(self.num_envs, self.action_dim, device=self.device)
-        self._processed_actions = torch.zeros_like(self.raw_actions)
-
-        # Get the simulation time step
-        self._sim_dt = env.sim.get_physics_dt()
-
-        self.total_time = 0  # Variable to accumulate the total time
-        self.num_runs = 0  # Counter for the number of runs
-
-        # Save the base_link_frame pose in the world frame as a transformation matrix in
-        # order to transform the desired pose of the controlled_frame to be with respect to the base_link_frame
-        # Shape of env.scene[self.cfg.articulation_name].data.body_link_state_w is (num_instances, num_bodies, 13)
-        base_link_frame_in_world_origin = env.scene[self.cfg.controller.articulation_name].data.body_link_state_w[
-            :,
-            env.scene[self.cfg.controller.articulation_name].data.body_names.index(self.cfg.controller.base_link_name),
-            :7,
-        ]
-
-        # Get robot base link frame in env origin frame
-        base_link_frame_in_env_origin = copy.deepcopy(base_link_frame_in_world_origin)
-        base_link_frame_in_env_origin[:, :3] -= self._env.scene.env_origins
-
-        self.base_link_frame_in_env_origin = math_utils.make_pose(
-            base_link_frame_in_env_origin[:, :3], math_utils.matrix_from_quat(base_link_frame_in_env_origin[:, 3:7])
-        )
-
-    # """
-    # Properties.
-    # """
-
-    @property
-    def hand_joint_dim(self) -> int:
-        """Dimension for hand joint positions."""
-        return self.cfg.controller.num_hand_joints
-
-    @property
-    def position_dim(self) -> int:
-        """Dimension for position (x, y, z)."""
-        return 3
-
-    @property
-    def orientation_dim(self) -> int:
-        """Dimension for orientation (w, x, y, z)."""
-        return 4
-
-    @property
-    def pose_dim(self) -> int:
-        """Total pose dimension (position + orientation)."""
-        return self.position_dim + self.orientation_dim
-
-    @property
-    def action_dim(self) -> int:
-        """Dimension of the action space (based on number of tasks and pose dimension)."""
-        # The tasks for all the controllers are the same, hence just using the first one to calculate the action_dim
-        return len(self._ik_controllers[0].cfg.variable_input_tasks) * self.pose_dim + self.hand_joint_dim
-
-    @property
-    def raw_actions(self) -> torch.Tensor:
-        """Get the raw actions tensor."""
-        return self._raw_actions
-
-    @property
-    def processed_actions(self) -> torch.Tensor:
-        """Get the processed actions tensor."""
-        return self._processed_actions
-
-    # """
-    # Operations.
-    # """
-
-    def process_actions(self, actions: torch.Tensor):
-        """Process the input actions and set targets for each task.
-
-        Args:
-            actions: The input actions tensor.
-        """
-        # Store the raw actions
-        self._raw_actions[:] = actions
-        self._processed_actions[:] = self.raw_actions
-
-        # Make a copy of actions before modifying so that raw actions are not modified
-        actions_clone = actions.clone()
-
-        # Extract hand joint positions (last 22 values)
-        self._target_hand_joint_positions = actions_clone[:, -self.hand_joint_dim :]
-
-        # The action tensor provides the desired pose of the controlled_frame with respect to the env origin frame
-        # But the pink IK controller expects the desired pose of the controlled_frame with respect to the base_link_frame
-        # So we need to transform the desired pose of the controlled_frame to be with respect to the base_link_frame
-
-        # Get the controlled_frame pose wrt to the env origin frame
-        all_controlled_frames_in_env_origin = []
-        # The contrllers for all envs are the same, hence just using the first one to get the number of variable_input_tasks
-        for task_index in range(len(self._ik_controllers[0].cfg.variable_input_tasks)):
-            controlled_frame_in_env_origin_pos = actions_clone[
-                :, task_index * self.pose_dim : task_index * self.pose_dim + self.position_dim
-            ]
-            controlled_frame_in_env_origin_quat = actions_clone[
-                :, task_index * self.pose_dim + self.position_dim : (task_index + 1) * self.pose_dim
-            ]
-            controlled_frame_in_env_origin = math_utils.make_pose(
-                controlled_frame_in_env_origin_pos, math_utils.matrix_from_quat(controlled_frame_in_env_origin_quat)
-            )
-            all_controlled_frames_in_env_origin.append(controlled_frame_in_env_origin)
-        # Stack all the controlled_frame poses in the env origin frame. Shape is (num_tasks, num_envs , 4, 4)
-        all_controlled_frames_in_env_origin = torch.stack(all_controlled_frames_in_env_origin)
-
-        # Transform the controlled_frame to be with respect to the base_link_frame using batched matrix multiplication
-        controlled_frame_in_base_link_frame = math_utils.pose_in_A_to_pose_in_B(
-            all_controlled_frames_in_env_origin, math_utils.pose_inv(self.base_link_frame_in_env_origin)
-        )
-
-        controlled_frame_in_base_link_frame_pos, controlled_frame_in_base_link_frame_mat = math_utils.unmake_pose(
-            controlled_frame_in_base_link_frame
-        )
-
-        # Loop through each task and set the target
-        for env_index, ik_controller in enumerate(self._ik_controllers):
-            for task_index, task in enumerate(ik_controller.cfg.variable_input_tasks):
-                target = task.transform_target_to_world
-                target.translation = controlled_frame_in_base_link_frame_pos[task_index, env_index, :].cpu().numpy()
-                target.rotation = controlled_frame_in_base_link_frame_mat[task_index, env_index, :].cpu().numpy()
-                task.set_target(target)
-
-    def apply_actions(self):
-        # start_time = time.time()  # Capture the time before the step
-        """Apply the computed joint positions based on the inverse kinematics solution."""
-        all_envs_joint_pos_des = []
-        for env_index, ik_controller in enumerate(self._ik_controllers):
-            curr_joint_pos = self._asset.data.joint_pos[:, self._pink_controlled_joint_ids].cpu().numpy()[env_index]
-            joint_pos_des = ik_controller.compute(curr_joint_pos, self._sim_dt)
-            all_envs_joint_pos_des.append(joint_pos_des)
-        all_envs_joint_pos_des = torch.stack(all_envs_joint_pos_des)
-        # Combine IK joint positions with hand joint positions
-        all_envs_joint_pos_des = torch.cat((all_envs_joint_pos_des, self._target_hand_joint_positions), dim=1)
-
-        self._asset.set_joint_position_target(all_envs_joint_pos_des, self._joint_ids)
-
-    def reset(self, env_ids: Sequence[int] | None = None) -> None:
-        """Reset the action term for specified environments.
-
-        Args:
-            env_ids: A list of environment IDs to reset. If None, all environments are reset.
-        """
-        self._raw_actions[env_ids] = torch.zeros(self.action_dim, device=self.device)
-
-
 class DifferentialInverseKinematicsAction(ActionTerm):
     r"""Inverse Kinematics action term.
 

source/isaaclab/setup.py

@@ -6,6 +6,7 @@
 """Installation script for the 'isaaclab' python package."""
 
 import os
+import platform
 import toml
 
 from setuptools import setup
@@ -39,10 +40,15 @@ INSTALL_REQUIRES = [
     # livestream
     "starlette==0.46.0",
     "flatdict==4.0.1",
-    "pin-pink==3.1.0",  # required by isaaclab.isaaclab.controllers.pink_ik
-    "dex-retargeting==0.4.6",  # required by isaaclab.devices.openxr.retargeters.humanoid.fourier.gr1_t2_dex_retargeting_utils
 ]
 
+# Additional dependencies that are only available on Linux platforms
+if platform.system() == "Linux":
+    INSTALL_REQUIRES += [
+        "pin-pink==3.1.0",  # required by isaaclab.isaaclab.controllers.pink_ik
+        "dex-retargeting==0.4.6",  # required by isaaclab.devices.openxr.retargeters.humanoid.fourier.gr1_t2_dex_retargeting_utils
+    ]
+
 PYTORCH_INDEX_URL = ["https://download.pytorch.org/whl/cu118"]
 
 # Installation operation

source/isaaclab_tasks/config/extension.toml

 [package]
 
 # Note: Semantic Versioning is used: https://semver.org/
-version = "0.10.28"
+version = "0.10.29"
 
 # Description
 title = "Isaac Lab Environments"

source/isaaclab_tasks/docs/CHANGELOG.rst

 Changelog
 ---------
 
-0.10.28 (2025-03-25)
+0.10.29 (2025-03-25)
 ~~~~~~~~~~~~~~~~~~~~
 
 Fixed
@@ -10,7 +10,7 @@ Fixed
 * Fixed environment test failure for ``Isaac-Stack-Cube-Franka-IK-Rel-Blueprint-v0``.
 
 
-0.10.27 (2025-03-18)
+0.10.28 (2025-03-18)
 ~~~~~~~~~~~~~~~~~~~~
 
 Added
@@ -19,6 +19,16 @@ Added
 * Added Gymnasium spaces showcase tasks (``Isaac-Cartpole-Showcase-*-Direct-v0``, and ``Isaac-Cartpole-Camera-Showcase-*-Direct-v0``).
 
 
+0.10.27 (2025-03-13)
+~~~~~~~~~~~~~~~~~~~~
+
+Fixed
+^^^^^
+
+* Blacklisted pick_place task from being imported automatically by isaaclab_tasks. It now has to be imported
+  manually by the script due to dependencies on the pinocchio import.
+
+
 0.10.26 (2025-03-10)
 ~~~~~~~~~~~~~~~~~~~~
 

source/isaaclab_tasks/isaaclab_tasks/__init__.py

@@ -25,6 +25,7 @@ __version__ = ISAACLAB_TASKS_METADATA["package"]["version"]
 from .utils import import_packages
 
 # The blacklist is used to prevent importing configs from sub-packages
-_BLACKLIST_PKGS = ["utils", ".mdp"]
+# TODO(@ashwinvk): Remove pick_place from the blacklist once pinocchio from Isaac Sim is compatibility
+_BLACKLIST_PKGS = ["utils", ".mdp", "pick_place"]
 # Import all configs in this package
 import_packages(__name__, _BLACKLIST_PKGS)

source/isaaclab_tasks/isaaclab_tasks/manager_based/manipulation/pick_place/pickplace_gr1t2_env_cfg.py

@@ -11,10 +11,10 @@ import isaaclab.controllers.utils as ControllerUtils
 import isaaclab.envs.mdp as base_mdp
 import isaaclab.sim as sim_utils
 from isaaclab.assets import ArticulationCfg, AssetBaseCfg, RigidObjectCfg
-from isaaclab.controllers import PinkIKControllerCfg
+from isaaclab.controllers.pink_ik_cfg import PinkIKControllerCfg
 from isaaclab.devices.openxr import XrCfg
 from isaaclab.envs import ManagerBasedRLEnvCfg
-from isaaclab.envs.mdp.actions.actions_cfg import PinkInverseKinematicsActionCfg
+from isaaclab.envs.mdp.actions.pink_actions_cfg import PinkInverseKinematicsActionCfg
 from isaaclab.managers import EventTermCfg as EventTerm
 from isaaclab.managers import ObservationGroupCfg as ObsGroup
 from isaaclab.managers import ObservationTermCfg as ObsTerm