isaac-sim · kellyguo11 · Mar 10, 2026 · Mar 6, 2026 · Mar 7, 2026 · Mar 7, 2026
@@ -118,7 +118,7 @@ jobs:
         image-tag: ${{ env.DOCKER_IMAGE_TAG }}
         pytest-options: ""
         filter-pattern: "isaaclab_tasks"
-        include-files: "test_multi_agent_environments.py,test_pickplace_stack_environments.py,test_environments.py,test_factory_environments.py,test_environments_training.py,test_cartpole_showcase_environments.py,test_teleop_environments.py"
+        include-files: "test_multi_agent_environments.py,test_pickplace_stack_environments.py,test_environments.py,test_environments_newton.py,test_factory_environments.py,test_environments_training.py,test_cartpole_showcase_environments.py,test_teleop_environments.py"
 
     - name: Upload IsaacLab Tasks Test Results
       uses: actions/upload-artifact@v4
@@ -179,7 +179,7 @@ jobs:
         image-tag: ${{ env.DOCKER_IMAGE_TAG }}
         pytest-options: ""
         filter-pattern: "isaaclab_tasks"
-        include-files: "test_teleop_environments_with_stage_in_memory.py,test_lift_teddy_bear.py,test_environment_determinism.py,test_hydra.py,test_env_cfg_no_forbidden_imports.py,test_rl_device_separation.py,test_cartpole_showcase_environments_with_stage_in_memory.py,test_environments_with_stage_in_memory.py"
+        include-files: "test_teleop_environments_with_stage_in_memory.py,test_lift_teddy_bear.py,test_environment_determinism.py,test_hydra.py,test_env_cfg_no_forbidden_imports.py,test_rl_device_separation.py,test_cartpole_showcase_environments_with_stage_in_memory.py,test_environments_with_stage_in_memory.py,test_shadow_hand_vision_presets.py"
 
     - name: Upload IsaacLab Tasks 2 Test Results
       uses: actions/upload-artifact@v4

@@ -386,7 +386,8 @@ def __call__(
         masses = torch.clamp(masses, min=min_mass)  # ensure masses are positive
 
         # set the mass into the physics simulation
-        self.asset.set_masses_index(masses=masses, env_ids=env_ids)
+        # note: backends expect partial data of shape (len(env_ids), len(body_ids))
+        self.asset.set_masses_index(masses=masses[env_ids[:, None], body_ids], body_ids=body_ids, env_ids=env_ids)
 
         # recompute inertia tensors if needed
         if recompute_inertia:
@@ -398,7 +399,10 @@ def __call__(
             # inertia has shape: (num_envs, num_bodies, 9) for all assets
             inertias[env_ids[:, None], body_ids] = self.default_inertia[env_ids[:, None], body_ids] * ratios[..., None]
             # set the inertia tensors into the physics simulation
-            self.asset.set_inertias_index(inertias=inertias, env_ids=env_ids)
+            # note: backends expect partial data of shape (len(env_ids), len(body_ids), 9)
+            self.asset.set_inertias_index(
+                inertias=inertias[env_ids[:, None], body_ids], body_ids=body_ids, env_ids=env_ids
+            )
 
 
 def randomize_rigid_body_com(

@@ -142,6 +142,15 @@ def __init__(self, cfg: SimulationCfg | None = None):
 
         # Initialize USD physics scene and physics manager
         self._init_usd_physics_scene()
+
+        # Normalize "cuda" -> "cuda:<id>" now that the USD physics scene is initialized
+        # and /physics/cudaDevice is available. Update cfg.device in-place so all
+        # downstream code (physics backends, assets, sensors) sees a consistent value.
+        if "cuda" in self.cfg.device and ":" not in self.cfg.device:
+            cuda_device = self.get_setting("/physics/cudaDevice")
+            device_id = max(0, int(cuda_device) if cuda_device is not None else 0)
+            self.cfg.device = f"cuda:{device_id}"
+
         # Set default physics backend if not specified
         if self.cfg.physics is None:
             from isaaclab_physx.physics import PhysxCfg

@@ -48,8 +48,9 @@
         "body": ImplicitActuatorCfg(
             joint_names_expr=[".*"],
             stiffness=0.0,
-            damping=0.0,
-            effort_limit_sim=30.0,
+            damping=0.1,
+            armature=0.05,
+            effort_limit_sim=15.0,
         ),
     },
 )

diff --git a/source/isaaclab_newton/config/extension.toml b/source/isaaclab_newton/config/extension.toml
@@ -1,7 +1,7 @@
 [package]
 
 # Note: Semantic Versioning is used: https://semver.org/
-version = "0.5.3"
+version = "0.5.4"
 
 # Description
 title = "Newton simulation interfaces for IsaacLab core package"

diff --git a/source/isaaclab_newton/docs/CHANGELOG.rst b/source/isaaclab_newton/docs/CHANGELOG.rst
@@ -37,6 +37,7 @@ Fixed
   spatial-vector extraction helpers. The ``source`` buffer shape and kernel dispatch ``dim``
   now use the input array's shape instead of the (possibly uninitialized) output shape.
 
+
 0.5.2 (2026-03-06)
 ~~~~~~~~~~~~~~~~~~
 
@@ -59,6 +60,7 @@ Fixed
   graph was not captured (e.g., when RTX/Fabric USD sync is active). The step condition now
   checks ``cls._graph is not None`` directly instead of repeating the capture-time heuristic.
 
+
 0.5.1 (2026-03-06)
 ~~~~~~~~~~~~~~~~~~
 

diff --git a/source/isaaclab_tasks/docs/CHANGELOG.rst b/source/isaaclab_tasks/docs/CHANGELOG.rst
@@ -36,15 +36,65 @@ Added
 * Added ``test_lazy_export_stubs.py`` to enforce that ``lazy_export()`` is called
   without arguments across the codebase.
 
-1.5.3 (2026-03-08)
+
+1.5.4 (2026-03-08)
+~~~~~~~~~~~~~~~~~~
+
+Added
+^^^^^
+
+* Added :file:`test/test_environments_newton.py` — an end-to-end CI test that auto-discovers
+  all environments with a ``newton`` physics preset and runs 100 random-action steps against each.
+
+* Added :func:`~isaaclab_tasks.utils.parse_cfg.apply_named_preset` helper that walks the full
+  configuration tree and applies a named preset (e.g. ``'newton'``) to every preset-wrapper
+  field, replacing the default-resolved value. This enables Newton preset overrides for all
+  scene fields (e.g. ``scene.contact_forces``) when running tests outside the Hydra pipeline.
+
+* Added Newton physics presets and compatibility fixes to locomotion, reach, Franka cabinet,
+  allegro-hand, and shadow-hand environments: replaced unsupported ``ls_iterations`` /
+  ``ls_parallel`` solver fields with Newton-compatible settings, and added a per-preset
+  :class:`~isaaclab_tasks.manager_based.manipulation.reach.reach_env_cfg.TableCfg` using box
+  geometry instead of a USD asset for Newton compatibility.
+
+* Added :class:`~isaaclab_tasks.manager_based.manipulation.cabinet.cabinet_env_cfg.CabinetSimCfg`
+  preset to the cabinet environment, replacing the physics-only preset with a full simulation
+  config preset so the Newton backend can run at a finer timestep (``dt=1/600``) while PhysX
+  keeps its default (``dt=1/60``).
+
+* Added backend-specific ``joint_gears`` to ant and humanoid direct environments. Newton and
+  PhysX joint orderings differ, so each backend now has its own gear ratio list resolved at
+  env init.
+
+
+1.5.3 (2026-03-06)
 ~~~~~~~~~~~~~~~~~~
 
 Fixed
 ^^^^^
 
-* Fixed ``TypeError: 'NoneType' object is not iterable`` in
-  :func:`~isaaclab_tasks.utils.hydra.apply_overrides` when a preset value is
-  ``None`` (e.g. ``default = None`` in a :class:`~isaaclab_tasks.utils.PresetCfg`).
+* Fixed :class:`~isaaclab.envs.mdp.noise.NoiseModelWithAdditiveBias` shape mismatch in Newton
+  environment tests. :func:`~isaaclab_tasks.utils.parse_cfg.apply_named_preset` previously
+  replaced ``scene`` with the preset's default ``num_envs`` (e.g. 8192), overwriting the
+  test-requested value (e.g. 2). The ``_bias`` tensor was then allocated with 8192 rows while
+  action data only had 2, causing a ``RuntimeError`` on addition. The fix re-applies the
+  caller's ``num_envs`` after preset application.
+
+* Fixed in-hand manipulation goal orientation: the quaternion imaginary-component clamping used
+  the wrong slice (``[1:4]`` instead of ``[0:3]``), causing incorrect goal distance computation
+  in the Newton preset.
+
+* Fixed Franka cabinet direct-env initialization orientation.
+
+Changed
+^^^^^^^
+
+* Renamed ``EventCfg`` to :class:`~isaaclab_tasks.direct.shadow_hand.shadow_hand_env_cfg.NewtonEventCfg`
+  in the Shadow Hand env config. The new name makes explicit that this preset covers only
+  Newton-compatible randomizations (joint gains, joint position limits, object mass, gravity).
+  Material and fixed-tendon randomization remain exclusively in
+  :class:`~isaaclab_tasks.direct.shadow_hand.shadow_hand_env_cfg.PhysxEventCfg`.
+
 
 1.5.2 (2026-03-05)
 ~~~~~~~~~~~~~~~~~~

@@ -74,8 +74,6 @@ class PhysicsCfg(PresetCfg):
             cone="elliptic",
             update_data_interval=2,
             iterations=100,
-            ls_iterations=15,
-            ls_parallel=False,
             # save_to_mjcf="AllegroHand.xml",
         ),
         num_substeps=2,

@@ -27,11 +27,9 @@ class AntPhysicsCfg(PresetCfg):
     physx: PhysxCfg = PhysxCfg()
     newton: NewtonCfg = NewtonCfg(
         solver_cfg=MJWarpSolverCfg(
-            njmax=38,
-            nconmax=15,
-            ls_iterations=20,
+            njmax=45,
+            nconmax=25,
             cone="pyramidal",
-            ls_parallel=True,
             integrator="implicitfast",
             impratio=1,
         ),

@@ -27,10 +27,8 @@ class CartpolePhysicsCfg(PresetCfg):
         solver_cfg=MJWarpSolverCfg(
             njmax=5,
             nconmax=3,
-            ls_iterations=10,
             cone="pyramidal",
             impratio=1,
-            ls_parallel=True,
             integrator="implicitfast",
         ),
         num_substeps=1,

@@ -102,7 +102,7 @@ class FrankaCabinetEnvCfg(DirectRLEnvCfg):
         ),
         init_state=ArticulationCfg.InitialStateCfg(
             pos=(0.0, 0, 0.4),
-            rot=(0.1, 0.0, 0.0, 0.0),
+            rot=(0.0, 0.0, 0.0, 1.0),
             joint_pos={
                 "door_left_joint": 0.0,
                 "door_right_joint": 0.0,

@@ -29,8 +29,6 @@ class HumanoidPhysicsCfg(PresetCfg):
         solver_cfg=MJWarpSolverCfg(
             njmax=80,
             nconmax=25,
-            ls_iterations=15,
-            ls_parallel=True,
             cone="pyramidal",
             update_data_interval=2,
             integrator="implicitfast",
@@ -74,7 +72,8 @@ class HumanoidEnvCfg(DirectRLEnvCfg):
 
     # robot
     robot: ArticulationCfg = HUMANOID_CFG.replace(prim_path="/World/envs/env_.*/Robot")
-    joint_gears: list = [
+
+    physx_joint_gears: list = [
         67.5000,  # lower_waist
         67.5000,  # lower_waist
         67.5000,  # right_upper_arm
@@ -97,6 +96,33 @@ class HumanoidEnvCfg(DirectRLEnvCfg):
         22.5,  # left_foot
         22.5,  # left_foot
     ]
+    newton_joint_gears: list = [
+        67.5000,  # left_upper_arm
+        67.5000,  # left_upper_arm
+        45.0000,  # left_lower_arm
+        67.5000,  # lower_waist
+        67.5000,  # lower_waist
+        67.5000,  # pelvis
+        45.0000,  # left_thigh: x
+        135.0000,  # left_thigh: y
+        45.0000,  # left_thigh: z
+        90.0000,  # left_knee
+        22.5,  # left_foot
+        22.5,  # left_foot
+        45.0000,  # right_thigh: x
+        135.0000,  # right_thigh: y
+        45.0000,  # right_thigh: z
+        90.0000,  # right_knee
+        22.5,  # right_foot
+        22.5,  # right_foot
+        67.5000,  # right_upper_arm
+        67.5000,  # right_upper_arm
+        45.0000,  # right_lower_arm
+    ]
+    joint_gears = {
+        "physx": physx_joint_gears,
+        "newton": newton_joint_gears,
+    }
 
     heading_weight: float = 0.5
     up_weight: float = 0.1

@@ -393,9 +393,7 @@ def randomize_rotation(rand0, rand1, x_unit_tensor, y_unit_tensor):
 def rotation_distance(object_rot, target_rot):
     # Orientation alignment for the cube in hand and goal cube
     quat_diff = quat_mul(object_rot, quat_conjugate(target_rot))
-    return 2.0 * torch.asin(
-        torch.clamp(torch.linalg.norm(quat_diff[:, 1:4], ord=2, dim=-1), max=1.0)
-    )  # changed quat convention
+    return 2.0 * torch.asin(torch.clamp(torch.linalg.norm(quat_diff[:, 0:3], ord=2, dim=-1), max=1.0))
 
 
 @torch.jit.script

@@ -7,6 +7,8 @@
 
 import torch
 import warp as wp
+from isaaclab_newton.physics import NewtonCfg
+from isaaclab_physx.physics import PhysxCfg
 
 import isaaclab.sim as sim_utils
 from isaaclab.assets import Articulation
@@ -75,7 +77,17 @@ def __init__(self, cfg: DirectRLEnvCfg, render_mode: str | None = None, **kwargs
         super().__init__(cfg, render_mode, **kwargs)
 
         self.action_scale = self.cfg.action_scale
-        self.joint_gears = torch.tensor(self.cfg.joint_gears, dtype=torch.float32, device=self.sim.device)
+        # Resolve the joint gears based on the physics type, since they do not have the same joint ordering.
+        if isinstance(self.cfg.joint_gears, dict):
+            if isinstance(self.cfg.sim.physics, PhysxCfg):
+                joint_gears = self.cfg.joint_gears["physx"]
+            elif isinstance(self.cfg.sim.physics, NewtonCfg):
+                joint_gears = self.cfg.joint_gears["newton"]
+            else:
+                raise ValueError(f"Invalid physics type: {self.cfg.sim.physics}")
+        else:
+            joint_gears = self.cfg.joint_gears
+        self.joint_gears = torch.tensor(joint_gears, dtype=torch.float32, device=self.sim.device)
         self.motor_effort_ratio = torch.ones_like(self.joint_gears, device=self.sim.device)
         self._joint_dof_idx, _ = self.robot.find_joints(".*")
 

@@ -27,8 +27,13 @@
 
 
 @configclass
-class EventCfg:
-    """Configuration for randomization."""
+class NewtonEventCfg:
+    """Event randomization config for the Newton physics backend.
+
+    Includes joint-parameter, mass, and gravity randomization.
+    Material and tendon randomization are omitted: Newton does not expose
+    per-body friction-material buckets or fixed-tendon APIs.
+    """
 
     robot_joint_stiffness_and_damping = EventTerm(
         func=mdp.randomize_actuator_gains,
@@ -42,19 +47,6 @@ class EventCfg:
             "distribution": "log_uniform",
         },
     )
-    robot_joint_pos_limits = EventTerm(
-        func=mdp.randomize_joint_parameters,
-        min_step_count_between_reset=720,
-        mode="reset",
-        params={
-            "asset_cfg": SceneEntityCfg("robot", joint_names=".*"),
-            "lower_limit_distribution_params": (0.00, 0.01),
-            "upper_limit_distribution_params": (0.00, 0.01),
-            "operation": "add",
-            "distribution": "gaussian",
-        },
-    )
-
     object_scale_mass = EventTerm(
         func=mdp.randomize_rigid_body_mass,
         min_step_count_between_reset=720,
@@ -64,6 +56,7 @@ class EventCfg:
             "mass_distribution_params": (0.5, 1.5),
             "operation": "scale",
             "distribution": "uniform",
+            "recompute_inertia": False,
         },
     )
 
@@ -127,7 +120,7 @@ class PhysxEventCfg:
 @configclass
 class ShadowHandEventCfg(PresetCfg):
     physx = PhysxEventCfg()
-    newton = EventCfg()
+    newton = NewtonEventCfg()
     default = physx
 
 
@@ -274,8 +267,6 @@ class PhysicsCfg(PresetCfg):
             cone="elliptic",
             update_data_interval=2,
             iterations=100,
-            ls_iterations=15,
-            ls_parallel=False,
         ),
         num_substeps=2,
         debug_mode=False,

@@ -36,9 +36,7 @@ class AntPhysicsCfg(PresetCfg):
         solver_cfg=MJWarpSolverCfg(
             njmax=38,
             nconmax=15,
-            ls_iterations=20,
             cone="pyramidal",
-            ls_parallel=True,
             integrator="implicitfast",
             impratio=1,
         ),

@@ -42,10 +42,8 @@ class CartpolePhysicsCfg(PresetCfg):
         solver_cfg=MJWarpSolverCfg(
             njmax=5,
             nconmax=3,
-            ls_iterations=10,
             cone="pyramidal",
             impratio=1,
-            ls_parallel=True,
             integrator="implicitfast",
         ),
         num_substeps=1,

@@ -33,8 +33,6 @@ class HumanoidPhysicsCfg(PresetCfg):
         solver_cfg=MJWarpSolverCfg(
             njmax=80,
             nconmax=25,
-            ls_iterations=15,
-            ls_parallel=True,
             cone="pyramidal",
             update_data_interval=2,
             integrator="implicitfast",