Adds a Franka stacking ManagerBasedRLEnv (#1494)

# Description

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to check the contribution guidelines.

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This PR adds a new ManagerBasedRLEnv for a three cube stacking task with
a Franka arm.

Docs updated to add new environment type and env tested with
test_environments.py script.

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discussions on the proposed pull request.
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## Type of change

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applicable. -->

- New feature (non-breaking change which adds functionality)
- This change requires a documentation update

## Screenshots

![franka_stack](https://github.com/user-attachments/assets/2f14059c-1117-44f1-87db-c6b5aaab2a11)


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## Checklist

- [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
- [ ] I have added tests that prove my fix is effective or that my
feature works
- [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

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---------
Co-authored-by: Kelly Guo <kellyg@nvidia.com>

CONTRIBUTORS.md

@@ -65,6 +65,7 @@ Guidelines for modifications:
 * Nuralem Abizov
 * Oyindamola Omotuyi
 * Özhan Özen
+* Peter Du
 * Qian Wan
 * Qinxi Yu
 * René Zurbrügg

docs/source/overview/environments.rst

@@ -109,6 +109,8 @@ for the reach environment:
     +--------------------+-------------------------+-----------------------------------------------------------------------------+
     | |lift-cube|        | |lift-cube-link|        | Pick a cube and bring it to a sampled target position with the Franka robot |
     +--------------------+-------------------------+-----------------------------------------------------------------------------+
+    | |stack-cube|       | |stack-cube-link|       | Stack three cubes (bottom to top: blue, red, green) with the Franka robot   |
+    +--------------------+-------------------------+-----------------------------------------------------------------------------+
     | |cabi-franka|      | |cabi-franka-link|      | Grasp the handle of a cabinet's drawer and open it with the Franka robot    |
     |                    |                         |                                                                             |
     |                    | |franka-direct-link|    |                                                                             |
@@ -132,6 +134,7 @@ for the reach environment:
 .. |cabi-franka| image:: ../_static/tasks/manipulation/franka_open_drawer.jpg
 .. |cube-allegro| image:: ../_static/tasks/manipulation/allegro_cube.jpg
 .. |cube-shadow| image:: ../_static/tasks/manipulation/shadow_cube.jpg
+.. |stack-franka| image:: ../_static/tasks/manipulation/franka_stack.jpg
 
 .. |reach-franka-link| replace:: `Isaac-Reach-Franka-v0 <https://github.com/isaac-sim/IsaacLab/blob/main/source/extensions/omni.isaac.lab_tasks/omni/isaac/lab_tasks/manager_based/manipulation/reach/config/franka/joint_pos_env_cfg.py>`__
 .. |reach-ur10-link| replace:: `Isaac-Reach-UR10-v0 <https://github.com/isaac-sim/IsaacLab/blob/main/source/extensions/omni.isaac.lab_tasks/omni/isaac/lab_tasks/manager_based/manipulation/reach/config/ur_10/joint_pos_env_cfg.py>`__
@@ -142,6 +145,7 @@ for the reach environment:
 .. |franka-direct-link| replace:: `Isaac-Franka-Cabinet-Direct-v0 <https://github.com/isaac-sim/IsaacLab/blob/main/source/extensions/omni.isaac.lab_tasks/omni/isaac/lab_tasks/direct/franka_cabinet/franka_cabinet_env.py>`__
 .. |cube-allegro-link| replace:: `Isaac-Repose-Cube-Allegro-v0 <https://github.com/isaac-sim/IsaacLab/blob/main/source/extensions/omni.isaac.lab_tasks/omni/isaac/lab_tasks/manager_based/manipulation/inhand/config/allegro_hand/allegro_env_cfg.py>`__
 .. |allegro-direct-link| replace:: `Isaac-Repose-Cube-Allegro-Direct-v0 <https://github.com/isaac-sim/IsaacLab/blob/main/source/extensions/omni.isaac.lab_tasks/omni/isaac/lab_tasks/direct/allegro_hand/allegro_hand_env_cfg.py>`__
+.. |stack-cube-link| replace:: `Isaac-Stack-Cube-Franka-v0 <https://github.com/isaac-sim/IsaacLab/blob/main/source/extensions/omni.isaac.lab_tasks/omni/isaac/lab_tasks/manager_based/manipulation/stack/config/franka/stack_joint_pos_env_cfg.py>`__
 
 .. |cube-shadow-link| replace:: `Isaac-Repose-Cube-Shadow-Direct-v0 <https://github.com/isaac-sim/IsaacLab/blob/main/source/extensions/omni.isaac.lab_tasks/omni/isaac/lab_tasks/direct/shadow_hand/shadow_hand_env_cfg.py>`__
 .. |cube-shadow-ff-link| replace:: `Isaac-Repose-Cube-Shadow-OpenAI-FF-Direct-v0 <https://github.com/isaac-sim/IsaacLab/blob/main/source/extensions/omni.isaac.lab_tasks/omni/isaac/lab_tasks/direct/shadow_hand/shadow_hand_env_cfg.py>`__

source/extensions/omni.isaac.lab_tasks/config/extension.toml

 [package]
 
 # Note: Semantic Versioning is used: https://semver.org/
-version = "0.10.13"
+version = "0.10.14"
 
 # Description
 title = "Isaac Lab Environments"

source/extensions/omni.isaac.lab_tasks/docs/CHANGELOG.rst

 Changelog
 ---------
 
+0.10.14 (2024-12-03)
+~~~~~~~~~~~~~~~~~~~~
+
+Added
+^^^^^
+
+* Added ``Isaac-Stack-Cube-Franka-IK-Rel-v0`` and ``Isaac-Stack-Cube-Instance-Randomize-Franka-IK-Rel-v0`` environments
+  as manager-based RL envs that implement a three cube stacking task.
+
 0.10.13 (2024-10-30)
 ~~~~~~~~~~~~~~~~~~~~
 

source/extensions/omni.isaac.lab_tasks/omni/isaac/lab_tasks/manager_based/manipulation/stack/__init__.py

+# Copyright (c) 2022-2024, The Isaac Lab Project Developers.
+# All rights reserved.
+#
+# SPDX-License-Identifier: BSD-3-Clause
+
+"""Configurations for the object stack environments."""
+
+# We leave this file empty since we don't want to expose any configs in this package directly.
+# We still need this file to import the "config" module in the parent package.

source/extensions/omni.isaac.lab_tasks/omni/isaac/lab_tasks/manager_based/manipulation/stack/config/__init__.py

+# Copyright (c) 2022-2024, The Isaac Lab Project Developers.
+# All rights reserved.
+#
+# SPDX-License-Identifier: BSD-3-Clause
+
+"""Configurations for the object stack environments."""
+
+# We leave this file empty since we don't want to expose any configs in this package directly.
+# We still need this file to import the "config" module in the parent package.

source/extensions/omni.isaac.lab_tasks/omni/isaac/lab_tasks/manager_based/manipulation/stack/config/franka/__init__.py

+# Copyright (c) 2022-2024, The Isaac Lab Project Developers.
+# All rights reserved.
+#
+# SPDX-License-Identifier: BSD-3-Clause
+import gymnasium as gym
+import os
+
+from . import (
+    agents,
+    stack_ik_rel_env_cfg,
+    stack_ik_rel_instance_randomize_env_cfg,
+    stack_joint_pos_env_cfg,
+    stack_joint_pos_instance_randomize_env_cfg,
+)
+
+##
+# Register Gym environments.
+##
+
+##
+# Joint Position Control
+##
+
+gym.register(
+    id="Isaac-Stack-Cube-Franka-v0",
+    entry_point="omni.isaac.lab.envs:ManagerBasedRLEnv",
+    kwargs={
+        "env_cfg_entry_point": stack_joint_pos_env_cfg.FrankaCubeStackEnvCfg,
+    },
+    disable_env_checker=True,
+)
+
+gym.register(
+    id="Isaac-Stack-Cube-Instance-Randomize-Franka-v0",
+    entry_point="omni.isaac.lab.envs:ManagerBasedRLEnv",
+    kwargs={
+        "env_cfg_entry_point": stack_joint_pos_instance_randomize_env_cfg.FrankaCubeStackInstanceRandomizeEnvCfg,
+    },
+    disable_env_checker=True,
+)
+
+
+##
+# Inverse Kinematics - Relative Pose Control
+##
+
+gym.register(
+    id="Isaac-Stack-Cube-Franka-IK-Rel-v0",
+    entry_point="omni.isaac.lab.envs:ManagerBasedRLEnv",
+    kwargs={
+        "env_cfg_entry_point": stack_ik_rel_env_cfg.FrankaCubeStackEnvCfg,
+        "robomimic_bc_cfg_entry_point": os.path.join(agents.__path__[0], "robomimic/bc_rnn_low_dim.json"),
+    },
+    disable_env_checker=True,
+)
+
+gym.register(
+    id="Isaac-Stack-Cube-Instance-Randomize-Franka-IK-Rel-v0",
+    entry_point="omni.isaac.lab.envs:ManagerBasedRLEnv",
+    kwargs={
+        "env_cfg_entry_point": stack_ik_rel_instance_randomize_env_cfg.FrankaCubeStackInstanceRandomizeEnvCfg,
+    },
+    disable_env_checker=True,
+)

source/extensions/omni.isaac.lab_tasks/omni/isaac/lab_tasks/manager_based/manipulation/stack/config/franka/agents/__init__.py

+# Copyright (c) 2022-2024, The Isaac Lab Project Developers.
+# All rights reserved.
+#
+# SPDX-License-Identifier: BSD-3-Clause

source/extensions/omni.isaac.lab_tasks/omni/isaac/lab_tasks/manager_based/manipulation/stack/config/franka/agents/robomimic/bc_rnn_low_dim.json

+{
+    "algo_name": "bc",
+    "experiment": {
+        "name": "bc",
+        "validate": false,
+        "logging": {
+            "terminal_output_to_txt": true,
+            "log_tb": true
+        },
+        "save": {
+            "enabled": true,
+            "every_n_seconds": null,
+            "every_n_epochs": 100,
+            "epochs": [],
+            "on_best_validation": false,
+            "on_best_rollout_return": false,
+            "on_best_rollout_success_rate": true
+        },
+        "epoch_every_n_steps": 100,
+        "env": null,
+        "additional_envs": null,
+        "render": false,
+        "render_video": false,
+        "rollout": {
+            "enabled": false
+        }
+    },
+    "train": {
+        "data": null,
+        "num_data_workers": 4,
+        "hdf5_cache_mode": "all",
+        "hdf5_use_swmr": true,
+        "hdf5_normalize_obs": false,
+        "hdf5_filter_key": null,
+        "hdf5_validation_filter_key": null,
+        "seq_length": 10,
+        "dataset_keys": [
+            "actions"
+        ],
+        "goal_mode": null,
+        "cuda": true,
+        "batch_size": 100,
+        "num_epochs": 2000,
+        "seed": 101
+    },
+    "algo": {
+        "optim_params": {
+            "policy": {
+                "optimizer_type": "adam",
+                "learning_rate": {
+                    "initial": 0.001,
+                    "decay_factor": 0.1,
+                    "epoch_schedule": [],
+                    "scheduler_type": "multistep"
+                },
+                "regularization": {
+                    "L2": 0.0
+                }
+            }
+        },
+        "loss": {
+            "l2_weight": 1.0,
+            "l1_weight": 0.0,
+            "cos_weight": 0.0
+        },
+        "actor_layer_dims": [],
+        "gmm": {
+            "enabled": true,
+            "num_modes": 5,
+            "min_std": 0.0001,
+            "std_activation": "softplus",
+            "low_noise_eval": true
+        },
+        "rnn": {
+            "enabled": true,
+            "horizon": 10,
+            "hidden_dim": 400,
+            "rnn_type": "LSTM",
+            "num_layers": 2,
+            "open_loop": false,
+            "kwargs": {
+                "bidirectional": false
+            }
+        }
+    },
+    "observation": {
+        "modalities": {
+            "obs": {
+                "low_dim": [
+                    "eef_pos",
+                    "eef_quat",
+                    "gripper_pos",
+                    "object"
+                ],
+                "rgb": [],
+                "depth": [],
+                "scan": []
+            }
+        }
+    }
+}

source/extensions/omni.isaac.lab_tasks/omni/isaac/lab_tasks/manager_based/manipulation/stack/config/franka/stack_ik_rel_env_cfg.py

+# Copyright (c) 2022-2024, The Isaac Lab Project Developers.
+# All rights reserved.
+#
+# SPDX-License-Identifier: BSD-3-Clause
+
+from omni.isaac.lab.controllers.differential_ik_cfg import DifferentialIKControllerCfg
+from omni.isaac.lab.envs.mdp.actions.actions_cfg import DifferentialInverseKinematicsActionCfg
+from omni.isaac.lab.utils import configclass
+
+from . import stack_joint_pos_env_cfg
+
+##
+# Pre-defined configs
+##
+from omni.isaac.lab_assets.franka import FRANKA_PANDA_HIGH_PD_CFG  # isort: skip
+
+
+@configclass
+class FrankaCubeStackEnvCfg(stack_joint_pos_env_cfg.FrankaCubeStackEnvCfg):
+    def __post_init__(self):
+        # post init of parent
+        super().__post_init__()
+
+        # Set Franka as robot
+        # We switch here to a stiffer PD controller for IK tracking to be better.
+        self.scene.robot = FRANKA_PANDA_HIGH_PD_CFG.replace(prim_path="{ENV_REGEX_NS}/Robot")
+
+        # Set actions for the specific robot type (franka)
+        self.actions.arm_action = DifferentialInverseKinematicsActionCfg(
+            asset_name="robot",
+            joint_names=["panda_joint.*"],
+            body_name="panda_hand",
+            controller=DifferentialIKControllerCfg(command_type="pose", use_relative_mode=True, ik_method="dls"),
+            scale=0.5,
+            body_offset=DifferentialInverseKinematicsActionCfg.OffsetCfg(pos=[0.0, 0.0, 0.107]),
+        )

source/extensions/omni.isaac.lab_tasks/omni/isaac/lab_tasks/manager_based/manipulation/stack/config/franka/stack_ik_rel_instance_randomize_env_cfg.py

+# Copyright (c) 2022-2024, The Isaac Lab Project Developers.
+# All rights reserved.
+#
+# SPDX-License-Identifier: BSD-3-Clause
+
+from omni.isaac.lab.controllers.differential_ik_cfg import DifferentialIKControllerCfg
+from omni.isaac.lab.envs.mdp.actions.actions_cfg import DifferentialInverseKinematicsActionCfg
+from omni.isaac.lab.utils import configclass
+
+from . import stack_joint_pos_instance_randomize_env_cfg
+
+##
+# Pre-defined configs
+##
+from omni.isaac.lab_assets.franka import FRANKA_PANDA_HIGH_PD_CFG  # isort: skip
+
+
+@configclass
+class FrankaCubeStackInstanceRandomizeEnvCfg(
+    stack_joint_pos_instance_randomize_env_cfg.FrankaCubeStackInstanceRandomizeEnvCfg
+):
+    def __post_init__(self):
+        # post init of parent
+        super().__post_init__()
+
+        # Set Franka as robot
+        # We switch here to a stiffer PD controller for IK tracking to be better.
+        self.scene.robot = FRANKA_PANDA_HIGH_PD_CFG.replace(prim_path="{ENV_REGEX_NS}/Robot")
+
+        # Set actions for the specific robot type (franka)
+        self.actions.arm_action = DifferentialInverseKinematicsActionCfg(
+            asset_name="robot",
+            joint_names=["panda_joint.*"],
+            body_name="panda_hand",
+            controller=DifferentialIKControllerCfg(command_type="pose", use_relative_mode=True, ik_method="dls"),
+            scale=0.5,
+            body_offset=DifferentialInverseKinematicsActionCfg.OffsetCfg(pos=[0.0, 0.0, 0.107]),
+        )

source/extensions/omni.isaac.lab_tasks/omni/isaac/lab_tasks/manager_based/manipulation/stack/config/franka/stack_joint_pos_env_cfg.py

+# Copyright (c) 2022-2024, The Isaac Lab Project Developers.
+# All rights reserved.
+#
+# SPDX-License-Identifier: BSD-3-Clause
+
+import omni.isaac.lab.sim as sim_utils
+from omni.isaac.lab.assets import RigidObjectCfg
+from omni.isaac.lab.managers import EventTermCfg as EventTerm
+from omni.isaac.lab.managers import SceneEntityCfg
+from omni.isaac.lab.sensors import CameraCfg, FrameTransformerCfg
+from omni.isaac.lab.sensors.frame_transformer.frame_transformer_cfg import OffsetCfg
+from omni.isaac.lab.sim.schemas.schemas_cfg import RigidBodyPropertiesCfg
+from omni.isaac.lab.sim.spawners.from_files.from_files_cfg import UsdFileCfg
+from omni.isaac.lab.utils import configclass
+from omni.isaac.lab.utils.assets import ISAAC_NUCLEUS_DIR
+
+from omni.isaac.lab_tasks.manager_based.manipulation.stack import mdp
+from omni.isaac.lab_tasks.manager_based.manipulation.stack.mdp import franka_stack_events
+from omni.isaac.lab_tasks.manager_based.manipulation.stack.stack_env_cfg import StackEnvCfg
+
+##
+# Pre-defined configs
+##
+from omni.isaac.lab.markers.config import FRAME_MARKER_CFG  # isort: skip
+from omni.isaac.lab_assets.franka import FRANKA_PANDA_CFG  # isort: skip
+
+
+@configclass
+class EventCfg:
+    """Configuration for events."""
+
+    init_franka_arm_pose = EventTerm(
+        func=franka_stack_events.set_default_joint_pose,
+        mode="startup",
+        params={
+            "default_pose": [0.0444, -0.1894, -0.1107, -2.5148, 0.0044, 2.3775, 0.6952, 0.0400, 0.0400],
+        },
+    )
+
+    randomize_franka_joint_state = EventTerm(
+        func=franka_stack_events.randomize_joint_by_gaussian_offset,
+        mode="reset",
+        params={
+            "mean": 0.0,
+            "std": 0.02,
+            "asset_cfg": SceneEntityCfg("robot"),
+        },
+    )
+
+    randomize_cube_positions = EventTerm(
+        func=franka_stack_events.randomize_object_pose,
+        mode="reset",
+        params={
+            "pose_range": {"x": (0.4, 0.6), "y": (-0.10, 0.10), "z": (0.0203, 0.0203), "yaw": (-1.0, 1, 0)},
+            "min_separation": 0.1,
+            "asset_cfgs": [SceneEntityCfg("cube_1"), SceneEntityCfg("cube_2"), SceneEntityCfg("cube_3")],
+        },
+    )
+
+
+@configclass
+class FrankaCubeStackEnvCfg(StackEnvCfg):
+    def __post_init__(self):
+        # post init of parent
+        super().__post_init__()
+
+        # Set events
+        self.events = EventCfg()
+
+        # Set Franka as robot
+        self.scene.robot = FRANKA_PANDA_CFG.replace(prim_path="{ENV_REGEX_NS}/Robot")
+
+        # Set actions for the specific robot type (franka)
+        self.actions.arm_action = mdp.JointPositionActionCfg(
+            asset_name="robot", joint_names=["panda_joint.*"], scale=0.5, use_default_offset=True
+        )
+        self.actions.gripper_action = mdp.BinaryJointPositionActionCfg(
+            asset_name="robot",
+            joint_names=["panda_finger.*"],
+            open_command_expr={"panda_finger_.*": 0.04},
+            close_command_expr={"panda_finger_.*": 0.0},
+        )
+
+        # Rigid body properties of each cube
+        cube_properties = RigidBodyPropertiesCfg(
+            solver_position_iteration_count=16,
+            solver_velocity_iteration_count=1,
+            max_angular_velocity=1000.0,
+            max_linear_velocity=1000.0,
+            max_depenetration_velocity=5.0,
+            disable_gravity=False,
+        )
+
+        # Set each stacking cube deterministically
+        self.scene.cube_1 = RigidObjectCfg(
+            prim_path="{ENV_REGEX_NS}/Cube_1",
+            init_state=RigidObjectCfg.InitialStateCfg(pos=[0.4, 0.0, 0.0203], rot=[1, 0, 0, 0]),
+            spawn=UsdFileCfg(
+                usd_path=f"{ISAAC_NUCLEUS_DIR}/Props/Blocks/blue_block.usd",
+                scale=(1.0, 1.0, 1.0),
+                rigid_props=cube_properties,
+            ),
+        )
+        self.scene.cube_2 = RigidObjectCfg(
+            prim_path="{ENV_REGEX_NS}/Cube_2",
+            init_state=RigidObjectCfg.InitialStateCfg(pos=[0.55, 0.05, 0.0203], rot=[1, 0, 0, 0]),
+            spawn=UsdFileCfg(
+                usd_path=f"{ISAAC_NUCLEUS_DIR}/Props/Blocks/red_block.usd",
+                scale=(1.0, 1.0, 1.0),
+                rigid_props=cube_properties,
+            ),
+        )
+        self.scene.cube_3 = RigidObjectCfg(
+            prim_path="{ENV_REGEX_NS}/Cube_3",
+            init_state=RigidObjectCfg.InitialStateCfg(pos=[0.60, -0.1, 0.0203], rot=[1, 0, 0, 0]),
+            spawn=UsdFileCfg(
+                usd_path=f"{ISAAC_NUCLEUS_DIR}/Props/Blocks/green_block.usd",
+                scale=(1.0, 1.0, 1.0),
+                rigid_props=cube_properties,
+            ),
+        )
+
+        # Set wrist camera
+        self.scene.wrist_cam = CameraCfg(
+            prim_path="{ENV_REGEX_NS}/Robot/panda_hand/wrist_cam",
+            update_period=0.0333,
+            height=84,
+            width=84,
+            data_types=["rgb", "distance_to_image_plane"],
+            spawn=sim_utils.PinholeCameraCfg(
+                focal_length=24.0, focus_distance=400.0, horizontal_aperture=20.955, clipping_range=(0.1, 1.0e5)
+            ),
+            offset=CameraCfg.OffsetCfg(pos=(0.025, 0.0, 0.0), rot=(0.707, 0.0, 0.0, 0.707), convention="ros"),
+        )
+
+        # Set table view camera
+        self.scene.table_cam = CameraCfg(
+            prim_path="{ENV_REGEX_NS}/table_cam",
+            update_period=0.0333,
+            height=84,
+            width=84,
+            data_types=["rgb", "distance_to_image_plane"],
+            spawn=sim_utils.PinholeCameraCfg(
+                focal_length=24.0, focus_distance=400.0, horizontal_aperture=20.955, clipping_range=(0.1, 1.0e5)
+            ),
+            offset=CameraCfg.OffsetCfg(pos=(1.0, 0.0, 0.33), rot=(-0.3799, 0.5963, 0.5963, -0.3799), convention="ros"),
+        )
+
+        # Listens to the required transforms
+        marker_cfg = FRAME_MARKER_CFG.copy()
+        marker_cfg.markers["frame"].scale = (0.1, 0.1, 0.1)
+        marker_cfg.prim_path = "/Visuals/FrameTransformer"
+        self.scene.ee_frame = FrameTransformerCfg(
+            prim_path="{ENV_REGEX_NS}/Robot/panda_link0",
+            debug_vis=False,
+            visualizer_cfg=marker_cfg,
+            target_frames=[
+                FrameTransformerCfg.FrameCfg(
+                    prim_path="{ENV_REGEX_NS}/Robot/panda_hand",
+                    name="end_effector",
+                    offset=OffsetCfg(
+                        pos=[0.0, 0.0, 0.1034],
+                    ),
+                ),
+                FrameTransformerCfg.FrameCfg(
+                    prim_path="{ENV_REGEX_NS}/Robot/panda_rightfinger",
+                    name="tool_rightfinger",
+                    offset=OffsetCfg(
+                        pos=(0.0, 0.0, 0.046),
+                    ),
+                ),
+                FrameTransformerCfg.FrameCfg(
+                    prim_path="{ENV_REGEX_NS}/Robot/panda_leftfinger",
+                    name="tool_leftfinger",
+                    offset=OffsetCfg(
+                        pos=(0.0, 0.0, 0.046),
+                    ),
+                ),
+            ],
+        )

source/extensions/omni.isaac.lab_tasks/omni/isaac/lab_tasks/manager_based/manipulation/stack/config/franka/stack_joint_pos_instance_randomize_env_cfg.py

+# Copyright (c) 2022-2024, The Isaac Lab Project Developers.
+# All rights reserved.
+#
+# SPDX-License-Identifier: BSD-3-Clause
+
+import torch
+
+import omni.isaac.lab.sim as sim_utils
+from omni.isaac.lab.assets import RigidObjectCfg, RigidObjectCollectionCfg
+from omni.isaac.lab.managers import EventTermCfg as EventTerm
+from omni.isaac.lab.managers import SceneEntityCfg
+from omni.isaac.lab.sensors import CameraCfg, FrameTransformerCfg
+from omni.isaac.lab.sensors.frame_transformer.frame_transformer_cfg import OffsetCfg
+from omni.isaac.lab.sim.schemas.schemas_cfg import RigidBodyPropertiesCfg
+from omni.isaac.lab.sim.spawners.from_files.from_files_cfg import UsdFileCfg
+from omni.isaac.lab.utils import configclass
+from omni.isaac.lab.utils.assets import ISAAC_NUCLEUS_DIR
+
+from omni.isaac.lab_tasks.manager_based.manipulation.stack import mdp
+from omni.isaac.lab_tasks.manager_based.manipulation.stack.mdp import franka_stack_events
+from omni.isaac.lab_tasks.manager_based.manipulation.stack.stack_instance_randomize_env_cfg import (
+    StackInstanceRandomizeEnvCfg,
+)
+
+##
+# Pre-defined configs
+##
+from omni.isaac.lab.markers.config import FRAME_MARKER_CFG  # isort: skip
+from omni.isaac.lab_assets.franka import FRANKA_PANDA_CFG  # isort: skip
+
+
+@configclass
+class EventCfg:
+    """Configuration for events."""
+
+    init_franka_arm_pose = EventTerm(
+        func=franka_stack_events.set_default_joint_pose,
+        mode="startup",
+        params={
+            "default_pose": [0.0444, -0.1894, -0.1107, -2.5148, 0.0044, 2.3775, 0.6952, 0.0400, 0.0400],
+        },
+    )
+
+    randomize_franka_joint_state = EventTerm(
+        func=franka_stack_events.randomize_joint_by_gaussian_offset,
+        mode="reset",
+        params={
+            "mean": 0.0,
+            "std": 0.02,
+            "asset_cfg": SceneEntityCfg("robot"),
+        },
+    )
+
+    randomize_cubes_in_focus = EventTerm(
+        func=franka_stack_events.randomize_rigid_objects_in_focus,
+        mode="reset",
+        params={
+            "asset_cfgs": [SceneEntityCfg("cube_1"), SceneEntityCfg("cube_2"), SceneEntityCfg("cube_3")],
+            "out_focus_state": torch.tensor([10.0, 10.0, 10.0, 1.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0]),
+            "pose_range": {"x": (0.4, 0.6), "y": (-0.10, 0.10), "z": (0.0203, 0.0203), "yaw": (-1.0, 1, 0)},
+            "min_separation": 0.1,
+        },
+    )
+
+
+@configclass
+class FrankaCubeStackInstanceRandomizeEnvCfg(StackInstanceRandomizeEnvCfg):
+    def __post_init__(self):
+        # post init of parent
+        super().__post_init__()
+
+        # Set events
+        self.events = EventCfg()
+
+        # Set Franka as robot
+        self.scene.robot = FRANKA_PANDA_CFG.replace(prim_path="{ENV_REGEX_NS}/Robot")
+
+        # Set actions for the specific robot type (franka)
+        self.actions.arm_action = mdp.JointPositionActionCfg(
+            asset_name="robot", joint_names=["panda_joint.*"], scale=0.5, use_default_offset=True
+        )
+        self.actions.gripper_action = mdp.BinaryJointPositionActionCfg(
+            asset_name="robot",
+            joint_names=["panda_finger.*"],
+            open_command_expr={"panda_finger_.*": 0.04},
+            close_command_expr={"panda_finger_.*": 0.0},
+        )
+
+        # Rigid body properties of each cube
+        cube_properties = RigidBodyPropertiesCfg(
+            solver_position_iteration_count=16,
+            solver_velocity_iteration_count=1,
+            max_angular_velocity=1000.0,
+            max_linear_velocity=1000.0,
+            max_depenetration_velocity=5.0,
+            disable_gravity=False,
+        )
+
+        # Set each stacking cube to be a collection of rigid objects
+        cube_1_config_dict = {
+            "blue_cube": RigidObjectCfg(
+                prim_path="{ENV_REGEX_NS}/Cube_1_Blue",
+                init_state=RigidObjectCfg.InitialStateCfg(pos=[0.4, 0.0, 0.0203], rot=[1, 0, 0, 0]),
+                spawn=UsdFileCfg(
+                    usd_path=f"{ISAAC_NUCLEUS_DIR}/Props/Blocks/blue_block.usd",
+                    scale=(1.0, 1.0, 1.0),
+                    rigid_props=cube_properties,
+                ),
+            ),
+            "red_cube": RigidObjectCfg(
+                prim_path="{ENV_REGEX_NS}/Cube_1_Red",
+                init_state=RigidObjectCfg.InitialStateCfg(pos=[0.4, 0.0, 0.0403], rot=[1, 0, 0, 0]),
+                spawn=UsdFileCfg(
+                    usd_path=f"{ISAAC_NUCLEUS_DIR}/Props/Blocks/red_block.usd",
+                    scale=(1.0, 1.0, 1.0),
+                    rigid_props=cube_properties,
+                ),
+            ),
+        }
+
+        cube_2_config_dict = {
+            "red_cube": RigidObjectCfg(
+                prim_path="{ENV_REGEX_NS}/Cube_2_Red",
+                init_state=RigidObjectCfg.InitialStateCfg(pos=[0.55, 0.05, 0.0203], rot=[1, 0, 0, 0]),
+                spawn=UsdFileCfg(
+                    usd_path=f"{ISAAC_NUCLEUS_DIR}/Props/Blocks/red_block.usd",
+                    scale=(1.0, 1.0, 1.0),
+                    rigid_props=cube_properties,
+                ),
+            ),
+            "yellow_cube": RigidObjectCfg(
+                prim_path="{ENV_REGEX_NS}/Cube_2_Yellow",
+                init_state=RigidObjectCfg.InitialStateCfg(pos=[0.55, 0.05, 0.0403], rot=[1, 0, 0, 0]),
+                spawn=UsdFileCfg(
+                    usd_path=f"{ISAAC_NUCLEUS_DIR}/Props/Blocks/yellow_block.usd",
+                    scale=(1.0, 1.0, 1.0),
+                    rigid_props=cube_properties,
+                ),
+            ),
+        }
+
+        cube_3_config_dict = {
+            "yellow_cube": RigidObjectCfg(
+                prim_path="{ENV_REGEX_NS}/Cube_3_Yellow",
+                init_state=RigidObjectCfg.InitialStateCfg(pos=[0.60, -0.1, 0.0203], rot=[1, 0, 0, 0]),
+                spawn=UsdFileCfg(
+                    usd_path=f"{ISAAC_NUCLEUS_DIR}/Props/Blocks/yellow_block.usd",
+                    scale=(1.0, 1.0, 1.0),
+                    rigid_props=cube_properties,
+                ),
+            ),
+            "green_cube": RigidObjectCfg(
+                prim_path="{ENV_REGEX_NS}/Cube_2_Green",
+                init_state=RigidObjectCfg.InitialStateCfg(pos=[0.60, -0.1, 0.0403], rot=[1, 0, 0, 0]),
+                spawn=UsdFileCfg(
+                    usd_path=f"{ISAAC_NUCLEUS_DIR}/Props/Blocks/green_block.usd",
+                    scale=(1.0, 1.0, 1.0),
+                    rigid_props=cube_properties,
+                ),
+            ),
+        }
+
+        self.scene.cube_1 = RigidObjectCollectionCfg(rigid_objects=cube_1_config_dict)
+        self.scene.cube_2 = RigidObjectCollectionCfg(rigid_objects=cube_2_config_dict)
+        self.scene.cube_3 = RigidObjectCollectionCfg(rigid_objects=cube_3_config_dict)
+
+        # Set wrist camera
+        self.scene.wrist_cam = CameraCfg(
+            prim_path="{ENV_REGEX_NS}/Robot/panda_hand/wrist_cam",
+            update_period=0.0333,
+            height=84,
+            width=84,
+            data_types=["rgb", "distance_to_image_plane"],
+            spawn=sim_utils.PinholeCameraCfg(
+                focal_length=24.0, focus_distance=400.0, horizontal_aperture=20.955, clipping_range=(0.1, 1.0e5)
+            ),
+            offset=CameraCfg.OffsetCfg(pos=(0.025, 0.0, 0.0), rot=(0.707, 0.0, 0.0, 0.707), convention="ros"),
+        )
+
+        # Set table view camera
+        self.scene.table_cam = CameraCfg(
+            prim_path="{ENV_REGEX_NS}/table_cam",
+            update_period=0.0333,
+            height=84,
+            width=84,
+            data_types=["rgb", "distance_to_image_plane"],
+            spawn=sim_utils.PinholeCameraCfg(
+                focal_length=24.0, focus_distance=400.0, horizontal_aperture=20.955, clipping_range=(0.1, 1.0e5)
+            ),
+            offset=CameraCfg.OffsetCfg(pos=(1.0, 0.0, 0.33), rot=(-0.3799, 0.5963, 0.5963, -0.3799), convention="ros"),
+        )
+
+        # Listens to the required transforms
+        marker_cfg = FRAME_MARKER_CFG.copy()
+        marker_cfg.markers["frame"].scale = (0.1, 0.1, 0.1)
+        marker_cfg.prim_path = "/Visuals/FrameTransformer"
+        self.scene.ee_frame = FrameTransformerCfg(
+            prim_path="{ENV_REGEX_NS}/Robot/panda_link0",
+            debug_vis=False,
+            visualizer_cfg=marker_cfg,
+            target_frames=[
+                FrameTransformerCfg.FrameCfg(
+                    prim_path="{ENV_REGEX_NS}/Robot/panda_hand",
+                    name="end_effector",
+                    offset=OffsetCfg(
+                        pos=[0.0, 0.0, 0.1034],
+                    ),
+                ),
+                FrameTransformerCfg.FrameCfg(
+                    prim_path="{ENV_REGEX_NS}/Robot/panda_rightfinger",
+                    name="tool_rightfinger",
+                    offset=OffsetCfg(
+                        pos=(0.0, 0.0, 0.046),
+                    ),
+                ),
+                FrameTransformerCfg.FrameCfg(
+                    prim_path="{ENV_REGEX_NS}/Robot/panda_leftfinger",
+                    name="tool_leftfinger",
+                    offset=OffsetCfg(
+                        pos=(0.0, 0.0, 0.046),
+                    ),
+                ),
+            ],
+        )

source/extensions/omni.isaac.lab_tasks/omni/isaac/lab_tasks/manager_based/manipulation/stack/mdp/__init__.py

+# Copyright (c) 2022-2024, The Isaac Lab Project Developers.
+# All rights reserved.
+#
+# SPDX-License-Identifier: BSD-3-Clause
+
+"""This sub-module contains the functions that are specific to the lift environments."""
+
+from omni.isaac.lab.envs.mdp import *  # noqa: F401, F403
+
+from .observations import *  # noqa: F401, F403
+from .terminations import *  # noqa: F401, F403

source/extensions/omni.isaac.lab_tasks/omni/isaac/lab_tasks/manager_based/manipulation/stack/mdp/franka_stack_events.py

+# Copyright (c) 2022-2024, The Isaac Lab Project Developers.
+# All rights reserved.
+#
+# SPDX-License-Identifier: BSD-3-Clause
+
+
+from __future__ import annotations
+
+import math
+import random
+import torch
+from typing import TYPE_CHECKING
+
+import omni.isaac.lab.utils.math as math_utils
+from omni.isaac.lab.assets import Articulation, AssetBase
+from omni.isaac.lab.managers import SceneEntityCfg
+
+if TYPE_CHECKING:
+    from omni.isaac.lab.envs import ManagerBasedEnv
+
+
+def set_default_joint_pose(
+    env: ManagerBasedEnv,
+    env_ids: torch.Tensor,
+    default_pose: torch.Tensor,
+    asset_cfg: SceneEntityCfg = SceneEntityCfg("robot"),
+):
+    # Set the default pose for robots in all envs
+    asset = env.scene[asset_cfg.name]
+    asset.data.default_joint_pos = torch.tensor(default_pose, device=env.device).repeat(env.num_envs, 1)
+
+
+def randomize_joint_by_gaussian_offset(
+    env: ManagerBasedEnv,
+    env_ids: torch.Tensor,
+    mean: float,
+    std: float,
+    asset_cfg: SceneEntityCfg = SceneEntityCfg("robot"),
+):
+    asset: Articulation = env.scene[asset_cfg.name]
+
+    # Add gaussian noise to joint states
+    joint_pos = asset.data.default_joint_pos[env_ids].clone()
+    joint_vel = asset.data.default_joint_vel[env_ids].clone()
+    joint_pos += math_utils.sample_gaussian(mean, std, joint_pos.shape, joint_pos.device)
+
+    # Clamp joint pos to limits
+    joint_pos_limits = asset.data.soft_joint_pos_limits[env_ids]
+    joint_pos = joint_pos.clamp_(joint_pos_limits[..., 0], joint_pos_limits[..., 1])
+
+    # Don't noise the gripper poses
+    joint_pos[:, -2:] = asset.data.default_joint_pos[env_ids, -2:]
+
+    # Set into the physics simulation
+    asset.set_joint_position_target(joint_pos, env_ids=env_ids)
+    asset.set_joint_velocity_target(joint_vel, env_ids=env_ids)
+    asset.write_joint_state_to_sim(joint_pos, joint_vel, env_ids=env_ids)
+
+
+def randomize_scene_lighting_domelight(
+    env: ManagerBasedEnv,
+    env_ids: torch.Tensor,
+    intensity_range: tuple[float, float],
+    asset_cfg: SceneEntityCfg = SceneEntityCfg("light"),
+):
+    asset: AssetBase = env.scene[asset_cfg.name]
+    light_prim = asset.prims[0]
+
+    # Sample new light intensity
+    new_intensity = random.uniform(intensity_range[0], intensity_range[1])
+
+    # Set light intensity to light prim
+    intensity_attr = light_prim.GetAttribute("inputs:intensity")
+    intensity_attr.Set(new_intensity)
+
+
+def sample_object_poses(
+    num_objects: int,
+    min_separation: float = 0.0,
+    pose_range: dict[str, tuple[float, float]] = {},
+    max_sample_tries: int = 5000,
+):
+    range_list = [pose_range.get(key, (0.0, 0.0)) for key in ["x", "y", "z", "roll", "pitch", "yaw"]]
+    pose_list = []
+
+    for i in range(num_objects):
+        for j in range(max_sample_tries):
+            sample = [random.uniform(range[0], range[1]) for range in range_list]
+
+            # Accept pose if it is the first one, or if reached max num tries
+            if len(pose_list) == 0 or j == max_sample_tries - 1:
+                pose_list.append(sample)
+                break
+
+            # Check if pose of object is sufficiently far away from all other objects
+            separation_check = [math.dist(sample[:3], pose[:3]) > min_separation for pose in pose_list]
+            if False not in separation_check:
+                pose_list.append(sample)
+                break
+
+    return pose_list
+
+
+def randomize_object_pose(
+    env: ManagerBasedEnv,
+    env_ids: torch.Tensor,
+    asset_cfgs: list[SceneEntityCfg],
+    min_separation: float = 0.0,
+    pose_range: dict[str, tuple[float, float]] = {},
+    max_sample_tries: int = 5000,
+):
+    if env_ids is None:
+        return
+
+    # Randomize poses in each environment independently
+    for cur_env in env_ids.tolist():
+        pose_list = sample_object_poses(
+            num_objects=len(asset_cfgs),
+            min_separation=min_separation,
+            pose_range=pose_range,
+            max_sample_tries=max_sample_tries,
+        )
+
+        # Randomize pose for each object
+        for i in range(len(asset_cfgs)):
+            asset_cfg = asset_cfgs[i]
+            asset = env.scene[asset_cfg.name]
+
+            # Write pose to simulation
+            pose_tensor = torch.tensor([pose_list[i]], device=env.device)
+            positions = pose_tensor[:, 0:3] + env.scene.env_origins[cur_env, 0:3]
+            orientations = math_utils.quat_from_euler_xyz(pose_tensor[:, 3], pose_tensor[:, 4], pose_tensor[:, 5])
+            asset.write_root_pose_to_sim(
+                torch.cat([positions, orientations], dim=-1), env_ids=torch.tensor([cur_env], device=env.device)
+            )
+            asset.write_root_velocity_to_sim(
+                torch.zeros(1, 6, device=env.device), env_ids=torch.tensor([cur_env], device=env.device)
+            )
+
+
+def randomize_rigid_objects_in_focus(
+    env: ManagerBasedEnv,
+    env_ids: torch.Tensor,
+    asset_cfgs: list[SceneEntityCfg],
+    out_focus_state: torch.Tensor,
+    min_separation: float = 0.0,
+    pose_range: dict[str, tuple[float, float]] = {},
+    max_sample_tries: int = 5000,
+):
+    if env_ids is None:
+        return
+
+    # List of rigid objects in focus for each env (dim = [num_envs, num_rigid_objects])
+    env.rigid_objects_in_focus = []
+
+    for cur_env in env_ids.tolist():
+        # Sample in focus object poses
+        pose_list = sample_object_poses(
+            num_objects=len(asset_cfgs),
+            min_separation=min_separation,
+            pose_range=pose_range,
+            max_sample_tries=max_sample_tries,
+        )
+
+        selected_ids = []
+        for asset_idx in range(len(asset_cfgs)):
+            asset_cfg = asset_cfgs[asset_idx]
+            asset = env.scene[asset_cfg.name]
+
+            # Randomly select an object to bring into focus
+            object_id = random.randint(0, asset.num_objects - 1)
+            selected_ids.append(object_id)
+
+            # Create object state tensor
+            object_states = torch.stack([out_focus_state] * asset.num_objects).to(device=env.device)
+            pose_tensor = torch.tensor([pose_list[asset_idx]], device=env.device)
+            positions = pose_tensor[:, 0:3] + env.scene.env_origins[cur_env, 0:3]
+            orientations = math_utils.quat_from_euler_xyz(pose_tensor[:, 3], pose_tensor[:, 4], pose_tensor[:, 5])
+            object_states[object_id, 0:3] = positions
+            object_states[object_id, 3:7] = orientations
+
+            asset.write_object_state_to_sim(
+                object_state=object_states, env_ids=torch.tensor([cur_env], device=env.device)
+            )
+
+        env.rigid_objects_in_focus.append(selected_ids)

source/extensions/omni.isaac.lab_tasks/omni/isaac/lab_tasks/manager_based/manipulation/stack/mdp/terminations.py

+# Copyright (c) 2022-2024, The Isaac Lab Project Developers.
+# All rights reserved.
+#
+# SPDX-License-Identifier: BSD-3-Clause
+
+"""Common functions that can be used to activate certain terminations for the lift task.
+
+The functions can be passed to the :class:`omni.isaac.lab.managers.TerminationTermCfg` object to enable
+the termination introduced by the function.
+"""
+
+from __future__ import annotations
+
+import torch
+from typing import TYPE_CHECKING
+
+from omni.isaac.lab.assets import Articulation, RigidObject
+from omni.isaac.lab.managers import SceneEntityCfg
+
+if TYPE_CHECKING:
+    from omni.isaac.lab.envs import ManagerBasedRLEnv
+
+
+def cubes_stacked(
+    env: ManagerBasedRLEnv,
+    robot_cfg: SceneEntityCfg = SceneEntityCfg("robot"),
+    cube_1_cfg: SceneEntityCfg = SceneEntityCfg("cube_1"),
+    cube_2_cfg: SceneEntityCfg = SceneEntityCfg("cube_2"),
+    cube_3_cfg: SceneEntityCfg = SceneEntityCfg("cube_3"),
+    xy_threshold: float = 0.05,
+    height_threshold: float = 0.005,
+    height_diff: float = 0.0468,
+    gripper_open_val: torch.tensor = torch.tensor([0.04]),
+    atol=0.0001,
+    rtol=0.0001,
+):
+    robot: Articulation = env.scene[robot_cfg.name]
+    cube_1: RigidObject = env.scene[cube_1_cfg.name]
+    cube_2: RigidObject = env.scene[cube_2_cfg.name]
+    cube_3: RigidObject = env.scene[cube_3_cfg.name]
+
+    pos_diff_c12 = cube_1.data.root_pos_w - cube_2.data.root_pos_w
+    pos_diff_c23 = cube_2.data.root_pos_w - cube_3.data.root_pos_w
+
+    # Compute cube position difference in x-y plane
+    xy_dist_c12 = torch.norm(pos_diff_c12[:, :2], dim=1)
+    xy_dist_c23 = torch.norm(pos_diff_c23[:, :2], dim=1)
+
+    # Compute cube height difference
+    h_dist_c12 = torch.norm(pos_diff_c12[:, 2:], dim=1)
+    h_dist_c23 = torch.norm(pos_diff_c23[:, 2:], dim=1)
+
+    # Check cube positions
+    stacked = torch.logical_and(xy_dist_c12 < xy_threshold, xy_dist_c23 < xy_threshold)
+    stacked = torch.logical_and(h_dist_c12 - height_diff < height_threshold, stacked)
+    stacked = torch.logical_and(h_dist_c23 - height_diff < height_threshold, stacked)
+
+    # Check gripper positions
+    stacked = torch.logical_and(
+        torch.isclose(robot.data.joint_pos[:, -1], gripper_open_val.to(env.device), atol=atol, rtol=rtol), stacked
+    )
+    stacked = torch.logical_and(
+        torch.isclose(robot.data.joint_pos[:, -2], gripper_open_val.to(env.device), atol=atol, rtol=rtol), stacked
+    )
+
+    return stacked

source/extensions/omni.isaac.lab_tasks/omni/isaac/lab_tasks/manager_based/manipulation/stack/stack_env_cfg.py

+# Copyright (c) 2022-2024, The Isaac Lab Project Developers.
+# All rights reserved.
+#
+# SPDX-License-Identifier: BSD-3-Clause
+
+from dataclasses import MISSING
+
+import omni.isaac.lab.sim as sim_utils
+from omni.isaac.lab.assets import ArticulationCfg, AssetBaseCfg
+from omni.isaac.lab.envs import ManagerBasedRLEnvCfg
+from omni.isaac.lab.managers import ObservationGroupCfg as ObsGroup
+from omni.isaac.lab.managers import ObservationTermCfg as ObsTerm
+from omni.isaac.lab.managers import SceneEntityCfg
+from omni.isaac.lab.managers import TerminationTermCfg as DoneTerm
+from omni.isaac.lab.scene import InteractiveSceneCfg
+from omni.isaac.lab.sensors import CameraCfg
+from omni.isaac.lab.sensors.frame_transformer.frame_transformer_cfg import FrameTransformerCfg
+from omni.isaac.lab.sim.spawners.from_files.from_files_cfg import GroundPlaneCfg, UsdFileCfg
+from omni.isaac.lab.utils import configclass
+from omni.isaac.lab.utils.assets import ISAAC_NUCLEUS_DIR
+
+from . import mdp
+
+
+##
+# Scene definition
+##
+@configclass
+class ObjectTableSceneCfg(InteractiveSceneCfg):
+    """Configuration for the lift scene with a robot and a object.
+    This is the abstract base implementation, the exact scene is defined in the derived classes
+    which need to set the target object, robot and end-effector frames
+    """
+
+    # robots: will be populated by agent env cfg
+    robot: ArticulationCfg = MISSING
+    # end-effector sensor: will be populated by agent env cfg
+    ee_frame: FrameTransformerCfg = MISSING
+
+    # Cameras
+    wrist_cam: CameraCfg = MISSING
+    table_cam: CameraCfg = MISSING
+
+    # Table
+    table = AssetBaseCfg(
+        prim_path="{ENV_REGEX_NS}/Table",
+        init_state=AssetBaseCfg.InitialStateCfg(pos=[0.5, 0, 0], rot=[0.707, 0, 0, 0.707]),
+        spawn=UsdFileCfg(usd_path=f"{ISAAC_NUCLEUS_DIR}/Props/Mounts/SeattleLabTable/table_instanceable.usd"),
+    )
+
+    # plane
+    plane = AssetBaseCfg(
+        prim_path="/World/GroundPlane",
+        init_state=AssetBaseCfg.InitialStateCfg(pos=[0, 0, -1.05]),
+        spawn=GroundPlaneCfg(),
+    )
+
+    # lights
+    light = AssetBaseCfg(
+        prim_path="/World/light",
+        spawn=sim_utils.DomeLightCfg(color=(0.75, 0.75, 0.75), intensity=3000.0),
+    )
+
+
+##
+# MDP settings
+##
+@configclass
+class ActionsCfg:
+    """Action specifications for the MDP."""
+
+    # will be set by agent env cfg
+    arm_action: mdp.JointPositionActionCfg = MISSING
+    gripper_action: mdp.BinaryJointPositionActionCfg = MISSING
+
+
+@configclass
+class ObservationsCfg:
+    """Observation specifications for the MDP."""
+
+    @configclass
+    class PolicyCfg(ObsGroup):
+        """Observations for policy group with state values."""
+
+        actions = ObsTerm(func=mdp.last_action)
+        joint_pos = ObsTerm(func=mdp.joint_pos_rel)
+        joint_vel = ObsTerm(func=mdp.joint_vel_rel)
+        object = ObsTerm(func=mdp.object_obs)
+        cube_positions = ObsTerm(func=mdp.cube_positions_in_world_frame)
+        cube_orientations = ObsTerm(func=mdp.cube_orientations_in_world_frame)
+        eef_pos = ObsTerm(func=mdp.ee_frame_pos)
+        eef_quat = ObsTerm(func=mdp.ee_frame_quat)
+        gripper_pos = ObsTerm(func=mdp.gripper_pos)
+
+        def __post_init__(self):
+            self.enable_corruption = False
+            self.concatenate_terms = False
+
+    @configclass
+    class RGBCameraPolicyCfg(ObsGroup):
+        """Observations for policy group with RGB images."""
+
+        table_cam = ObsTerm(
+            func=mdp.image, params={"sensor_cfg": SceneEntityCfg("table_cam"), "data_type": "rgb", "normalize": False}
+        )
+        wrist_cam = ObsTerm(
+            func=mdp.image, params={"sensor_cfg": SceneEntityCfg("wrist_cam"), "data_type": "rgb", "normalize": False}
+        )
+
+        def __post_init__(self):
+            self.enable_corruption = False
+            self.concatenate_terms = False
+
+    @configclass
+    class SubtaskCfg(ObsGroup):
+        """Observations for subtask group."""
+
+        grasp_1 = ObsTerm(
+            func=mdp.object_grasped,
+            params={
+                "robot_cfg": SceneEntityCfg("robot"),
+                "ee_frame_cfg": SceneEntityCfg("ee_frame"),
+                "object_cfg": SceneEntityCfg("cube_2"),
+            },
+        )
+        stack_1 = ObsTerm(
+            func=mdp.object_stacked,
+            params={
+                "robot_cfg": SceneEntityCfg("robot"),
+                "upper_object_cfg": SceneEntityCfg("cube_2"),
+                "lower_object_cfg": SceneEntityCfg("cube_1"),
+            },
+        )
+        grasp_2 = ObsTerm(
+            func=mdp.object_grasped,
+            params={
+                "robot_cfg": SceneEntityCfg("robot"),
+                "ee_frame_cfg": SceneEntityCfg("ee_frame"),
+                "object_cfg": SceneEntityCfg("cube_3"),
+            },
+        )
+
+        def __post_init__(self):
+            self.enable_corruption = False
+            self.concatenate_terms = False
+
+    # observation groups
+    policy: PolicyCfg = PolicyCfg()
+    rgb_camera: RGBCameraPolicyCfg = RGBCameraPolicyCfg()
+    subtask_terms: SubtaskCfg = SubtaskCfg()
+
+
+@configclass
+class TerminationsCfg:
+    """Termination terms for the MDP."""
+
+    time_out = DoneTerm(func=mdp.time_out, time_out=True)
+
+    cube_1_dropping = DoneTerm(
+        func=mdp.root_height_below_minimum, params={"minimum_height": -0.05, "asset_cfg": SceneEntityCfg("cube_1")}
+    )
+
+    cube_2_dropping = DoneTerm(
+        func=mdp.root_height_below_minimum, params={"minimum_height": -0.05, "asset_cfg": SceneEntityCfg("cube_2")}
+    )
+
+    cube_3_dropping = DoneTerm(
+        func=mdp.root_height_below_minimum, params={"minimum_height": -0.05, "asset_cfg": SceneEntityCfg("cube_3")}
+    )
+
+    success = DoneTerm(func=mdp.cubes_stacked)
+
+
+@configclass
+class StackEnvCfg(ManagerBasedRLEnvCfg):
+    """Configuration for the stacking environment."""
+
+    # Scene settings
+    scene: ObjectTableSceneCfg = ObjectTableSceneCfg(num_envs=4096, env_spacing=2.5, replicate_physics=False)
+    # Basic settings
+    observations: ObservationsCfg = ObservationsCfg()
+    actions: ActionsCfg = ActionsCfg()
+    # MDP settings
+    terminations: TerminationsCfg = TerminationsCfg()
+
+    # Unused managers
+    commands = None
+    rewards = None
+    events = None
+    curriculum = None
+
+    def __post_init__(self):
+        """Post initialization."""
+        # general settings
+        self.decimation = 5
+        self.episode_length_s = 30.0
+        # simulation settings
+        self.sim.dt = 0.01  # 100Hz
+        self.sim.render_interval = self.decimation
+
+        self.sim.physx.bounce_threshold_velocity = 0.2
+        self.sim.physx.bounce_threshold_velocity = 0.01
+        self.sim.physx.gpu_found_lost_aggregate_pairs_capacity = 1024 * 1024 * 4
+        self.sim.physx.gpu_total_aggregate_pairs_capacity = 16 * 1024
+        self.sim.physx.friction_correlation_distance = 0.00625

source/extensions/omni.isaac.lab_tasks/omni/isaac/lab_tasks/manager_based/manipulation/stack/stack_instance_randomize_env_cfg.py

+# Copyright (c) 2022-2024, The Isaac Lab Project Developers.
+# All rights reserved.
+#
+# SPDX-License-Identifier: BSD-3-Clause
+
+from dataclasses import MISSING
+
+import omni.isaac.lab.sim as sim_utils
+from omni.isaac.lab.assets import ArticulationCfg, AssetBaseCfg
+from omni.isaac.lab.envs import ManagerBasedRLEnvCfg
+from omni.isaac.lab.managers import ObservationGroupCfg as ObsGroup
+from omni.isaac.lab.managers import ObservationTermCfg as ObsTerm
+from omni.isaac.lab.managers import SceneEntityCfg
+from omni.isaac.lab.managers import TerminationTermCfg as DoneTerm
+from omni.isaac.lab.scene import InteractiveSceneCfg
+from omni.isaac.lab.sensors import CameraCfg
+from omni.isaac.lab.sensors.frame_transformer.frame_transformer_cfg import FrameTransformerCfg
+from omni.isaac.lab.sim.spawners.from_files.from_files_cfg import GroundPlaneCfg, UsdFileCfg
+from omni.isaac.lab.utils import configclass
+from omni.isaac.lab.utils.assets import ISAAC_NUCLEUS_DIR
+
+from . import mdp
+
+
+##
+# Scene definition
+##
+@configclass
+class ObjectTableSceneCfg(InteractiveSceneCfg):
+    """Configuration for the lift scene with a robot and a object.
+    This is the abstract base implementation, the exact scene is defined in the derived classes
+    which need to set the target object, robot and end-effector frames
+    """
+
+    # robots: will be populated by agent env cfg
+    robot: ArticulationCfg = MISSING
+    # end-effector sensor: will be populated by agent env cfg
+    ee_frame: FrameTransformerCfg = MISSING
+
+    # Cameras
+    wrist_cam: CameraCfg = MISSING
+    table_cam: CameraCfg = MISSING
+
+    # Table
+    table = AssetBaseCfg(
+        prim_path="{ENV_REGEX_NS}/Table",
+        init_state=AssetBaseCfg.InitialStateCfg(pos=[0.5, 0, 0], rot=[0.707, 0, 0, 0.707]),
+        spawn=UsdFileCfg(usd_path=f"{ISAAC_NUCLEUS_DIR}/Props/Mounts/SeattleLabTable/table_instanceable.usd"),
+    )
+
+    # plane
+    plane = AssetBaseCfg(
+        prim_path="/World/GroundPlane",
+        init_state=AssetBaseCfg.InitialStateCfg(pos=[0, 0, -1.05]),
+        spawn=GroundPlaneCfg(),
+    )
+
+    # lights
+    light = AssetBaseCfg(
+        prim_path="/World/light",
+        spawn=sim_utils.DomeLightCfg(color=(0.75, 0.75, 0.75), intensity=3000.0),
+    )
+
+
+##
+# MDP settings
+##
+@configclass
+class ActionsCfg:
+    """Action specifications for the MDP."""
+
+    # will be set by agent env cfg
+    arm_action: mdp.JointPositionActionCfg = MISSING
+    gripper_action: mdp.BinaryJointPositionActionCfg = MISSING
+
+
+@configclass
+class ObservationsCfg:
+    """Observation specifications for the MDP."""
+
+    @configclass
+    class PolicyCfg(ObsGroup):
+        """Observations for policy group with state values."""
+
+        actions = ObsTerm(func=mdp.last_action)
+        joint_pos = ObsTerm(func=mdp.joint_pos_rel)
+        joint_vel = ObsTerm(func=mdp.joint_vel_rel)
+        object = ObsTerm(func=mdp.instance_randomize_object_obs)
+        cube_positions = ObsTerm(func=mdp.instance_randomize_cube_positions_in_world_frame)
+        cube_orientations = ObsTerm(func=mdp.instance_randomize_cube_orientations_in_world_frame)
+        eef_pos = ObsTerm(func=mdp.ee_frame_pos)
+        eef_quat = ObsTerm(func=mdp.ee_frame_quat)
+        gripper_pos = ObsTerm(func=mdp.gripper_pos)
+
+        def __post_init__(self):
+            self.enable_corruption = False
+            self.concatenate_terms = False
+
+    @configclass
+    class RGBCameraPolicyCfg(ObsGroup):
+        """Observations for policy group with RGB images."""
+
+        table_cam = ObsTerm(
+            func=mdp.image, params={"sensor_cfg": SceneEntityCfg("table_cam"), "data_type": "rgb", "normalize": False}
+        )
+        wrist_cam = ObsTerm(
+            func=mdp.image, params={"sensor_cfg": SceneEntityCfg("wrist_cam"), "data_type": "rgb", "normalize": False}
+        )
+
+        def __post_init__(self):
+            self.enable_corruption = False
+            self.concatenate_terms = False
+
+    # observation groups
+    policy: PolicyCfg = PolicyCfg()
+    rgb_camera: RGBCameraPolicyCfg = RGBCameraPolicyCfg()
+
+
+@configclass
+class TerminationsCfg:
+    """Termination terms for the MDP."""
+
+    time_out = DoneTerm(func=mdp.time_out, time_out=True)
+
+
+@configclass
+class StackInstanceRandomizeEnvCfg(ManagerBasedRLEnvCfg):
+    """Configuration for the stacking environment."""
+
+    # Scene settings
+    scene: ObjectTableSceneCfg = ObjectTableSceneCfg(num_envs=4096, env_spacing=2.5, replicate_physics=False)
+    # Basic settings
+    observations: ObservationsCfg = ObservationsCfg()
+    actions: ActionsCfg = ActionsCfg()
+    # MDP settings
+    terminations: TerminationsCfg = TerminationsCfg()
+
+    # Unused managers
+    commands = None
+    rewards = None
+    events = None
+    curriculum = None
+
+    def __post_init__(self):
+        """Post initialization."""
+        # general settings
+        self.decimation = 5
+        self.episode_length_s = 30.0
+        # simulation settings
+        self.sim.dt = 0.01  # 100Hz
+        self.sim.render_interval = self.decimation
+
+        self.sim.physx.bounce_threshold_velocity = 0.2
+        self.sim.physx.bounce_threshold_velocity = 0.01
+        self.sim.physx.gpu_found_lost_aggregate_pairs_capacity = 1024 * 1024 * 4
+        self.sim.physx.gpu_total_aggregate_pairs_capacity = 16 * 1024
+        self.sim.physx.friction_correlation_distance = 0.00625