Disables replicate physics for deformable teddy lift environment (#1026)

# Description

This MR fixes the teddy state machine example. Replicate physics doesn't
work for deformable bodies yet. Hence, calling more than one environment
was failing before. The flag is set to False now inside the post init of
the environment.

Fixes #1022

## Type of change

- Bug fix (non-breaking change which fixes an issue)

## 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
- [ ] 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

source/extensions/omni.isaac.lab/omni/isaac/lab/envs/mdp/events.py

@@ -24,7 +24,7 @@ import omni.physics.tensors.impl.api as physx
 import omni.isaac.lab.sim as sim_utils
 import omni.isaac.lab.utils.math as math_utils
 from omni.isaac.lab.actuators import ImplicitActuator
-from omni.isaac.lab.assets import Articulation, RigidObject
+from omni.isaac.lab.assets import Articulation, DeformableObject, RigidObject
 from omni.isaac.lab.managers import SceneEntityCfg
 from omni.isaac.lab.terrains import TerrainImporter
 
@@ -824,6 +824,48 @@ def reset_joints_by_offset(
     asset.write_joint_state_to_sim(joint_pos, joint_vel, env_ids=env_ids)
 
 
+def reset_nodal_state_uniform(
+    env: ManagerBasedEnv,
+    env_ids: torch.Tensor,
+    position_range: dict[str, tuple[float, float]],
+    velocity_range: dict[str, tuple[float, float]],
+    asset_cfg: SceneEntityCfg = SceneEntityCfg("robot"),
+):
+    """Reset the asset nodal state to a random position and velocity uniformly within the given ranges.
+
+    This function randomizes the nodal position and velocity of the asset.
+
+    * It samples the root position from the given ranges and adds them to the default nodal position, before setting
+      them into the physics simulation.
+    * It samples the root velocity from the given ranges and sets them into the physics simulation.
+
+    The function takes a dictionary of position and velocity ranges for each axis. The keys of the
+    dictionary are ``x``, ``y``, ``z``. The values are tuples of the form ``(min, max)``.
+    If the dictionary does not contain a key, the position or velocity is set to zero for that axis.
+    """
+    # extract the used quantities (to enable type-hinting)
+    asset: DeformableObject = env.scene[asset_cfg.name]
+    # get default root state
+    nodal_state = asset.data.default_nodal_state_w[env_ids].clone()
+
+    # position
+    range_list = [position_range.get(key, (0.0, 0.0)) for key in ["x", "y", "z"]]
+    ranges = torch.tensor(range_list, device=asset.device)
+    rand_samples = math_utils.sample_uniform(ranges[:, 0], ranges[:, 1], (len(env_ids), 1, 3), device=asset.device)
+
+    nodal_state[..., :3] += rand_samples
+
+    # velocities
+    range_list = [velocity_range.get(key, (0.0, 0.0)) for key in ["x", "y", "z"]]
+    ranges = torch.tensor(range_list, device=asset.device)
+    rand_samples = math_utils.sample_uniform(ranges[:, 0], ranges[:, 1], (len(env_ids), 1, 3), device=asset.device)
+
+    nodal_state[..., 3:] += rand_samples
+
+    # set into the physics simulation
+    asset.write_nodal_state_to_sim(nodal_state, env_ids=env_ids)
+
+
 def reset_scene_to_default(env: ManagerBasedEnv, env_ids: torch.Tensor):
     """Reset the scene to the default state specified in the scene configuration."""
     # rigid bodies
@@ -845,6 +887,11 @@ def reset_scene_to_default(env: ManagerBasedEnv, env_ids: torch.Tensor):
         default_joint_vel = articulation_asset.data.default_joint_vel[env_ids].clone()
         # set into the physics simulation
         articulation_asset.write_joint_state_to_sim(default_joint_pos, default_joint_vel, env_ids=env_ids)
+    # deformable objects
+    for deformable_object in env.scene.deformable_objects.values():
+        # obtain default and set into the physics simulation
+        nodal_state = deformable_object.data.default_nodal_state_w[env_ids].clone()
+        deformable_object.write_nodal_state_to_sim(nodal_state, env_ids=env_ids)
 
 
 """

source/extensions/omni.isaac.lab_tasks/omni/isaac/lab_tasks/manager_based/manipulation/lift/config/franka/ik_abs_env_cfg.py

@@ -6,10 +6,14 @@
 from omni.isaac.lab.assets import DeformableObjectCfg
 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.managers import EventTermCfg as EventTerm
+from omni.isaac.lab.managers import SceneEntityCfg
 from omni.isaac.lab.sim.spawners import UsdFileCfg
 from omni.isaac.lab.utils import configclass
 from omni.isaac.lab.utils.assets import ISAACLAB_NUCLEUS_DIR
 
+import omni.isaac.lab_tasks.manager_based.manipulation.lift.mdp as mdp
+
 from . import joint_pos_env_cfg
 
 ##
@@ -18,6 +22,11 @@ from . import joint_pos_env_cfg
 from omni.isaac.lab_assets.franka import FRANKA_PANDA_HIGH_PD_CFG  # isort: skip
 
 
+##
+# Rigid object lift environment.
+##
+
+
 @configclass
 class FrankaCubeLiftEnvCfg(joint_pos_env_cfg.FrankaCubeLiftEnvCfg):
     def __post_init__(self):
@@ -50,6 +59,11 @@ class FrankaCubeLiftEnvCfg_PLAY(FrankaCubeLiftEnvCfg):
         self.observations.policy.enable_corruption = False
 
 
+##
+# Deformable object lift environment.
+##
+
+
 @configclass
 class FrankaTeddyBearLiftEnvCfg(FrankaCubeLiftEnvCfg):
     def __post_init__(self):
@@ -58,7 +72,7 @@ class FrankaTeddyBearLiftEnvCfg(FrankaCubeLiftEnvCfg):
 
         self.scene.object = DeformableObjectCfg(
             prim_path="{ENV_REGEX_NS}/Object",
-            init_state=DeformableObjectCfg.InitialStateCfg(pos=[0.5, 0, 0.05], rot=[0.707, 0, 0, 0.707]),
+            init_state=DeformableObjectCfg.InitialStateCfg(pos=(0.5, 0, 0.05), rot=(0.707, 0, 0, 0.707)),
             spawn=UsdFileCfg(
                 usd_path=f"{ISAACLAB_NUCLEUS_DIR}/Objects/Teddy_Bear/teddy_bear.usd",
                 scale=(0.01, 0.01, 0.01),
@@ -70,11 +84,27 @@ class FrankaTeddyBearLiftEnvCfg(FrankaCubeLiftEnvCfg):
         self.scene.robot.actuators["panda_hand"].stiffness = 40.0
         self.scene.robot.actuators["panda_hand"].damping = 10.0
 
-        # Remove all the terms for the lift_teddy_bear_sm demo
+        # Disable replicate physics as it doesn't work for deformable objects
+        # FIXME: This should be fixed by the PhysX replication system.
+        self.scene.replicate_physics = False
+
+        # Set events for the specific object type (deformable cube)
+        self.events.reset_object_position = EventTerm(
+            func=mdp.reset_nodal_state_uniform,
+            mode="reset",
+            params={
+                "position_range": {"x": (-0.1, 0.1), "y": (-0.25, 0.25), "z": (0.0, 0.0)},
+                "velocity_range": {},
+                "asset_cfg": SceneEntityCfg("object"),
+            },
+        )
+
+        # Remove all the terms for the state machine demo
+        # TODO: Computing the root pose of deformable object from nodal positions is expensive.
+        #       We need to fix that part before enabling these terms for the training.
         self.terminations.object_dropping = None
         self.rewards.reaching_object = None
         self.rewards.lifting_object = None
         self.rewards.object_goal_tracking = None
         self.rewards.object_goal_tracking_fine_grained = None
-        self.events.reset_object_position = None
         self.observations.policy.object_position = None

source/extensions/omni.isaac.lab_tasks/omni/isaac/lab_tasks/manager_based/manipulation/lift/lift_env_cfg.py

@@ -6,7 +6,7 @@
 from dataclasses import MISSING
 
 import omni.isaac.lab.sim as sim_utils
-from omni.isaac.lab.assets import ArticulationCfg, AssetBaseCfg, RigidObjectCfg
+from omni.isaac.lab.assets import ArticulationCfg, AssetBaseCfg, DeformableObjectCfg, RigidObjectCfg
 from omni.isaac.lab.envs import ManagerBasedRLEnvCfg
 from omni.isaac.lab.managers import CurriculumTermCfg as CurrTerm
 from omni.isaac.lab.managers import EventTermCfg as EventTerm
@@ -40,7 +40,7 @@ class ObjectTableSceneCfg(InteractiveSceneCfg):
     # end-effector sensor: will be populated by agent env cfg
     ee_frame: FrameTransformerCfg = MISSING
     # target object: will be populated by agent env cfg
-    object: RigidObjectCfg = MISSING
+    object: RigidObjectCfg | DeformableObjectCfg = MISSING
 
     # Table
     table = AssetBaseCfg(
@@ -88,7 +88,7 @@ class ActionsCfg:
     """Action specifications for the MDP."""
 
     # will be set by agent env cfg
-    arm_action: mdp.JointPositionActionCfg = MISSING
+    arm_action: mdp.JointPositionActionCfg | mdp.DifferentialInverseKinematicsActionCfg = MISSING
     gripper_action: mdp.BinaryJointPositionActionCfg = MISSING