From e9e3834f59c6afffd493cd661210a7a71702d580 Mon Sep 17 00:00:00 2001
From: jichuanh <jichuanh@nvidia.com>
Date: Wed, 8 Jul 2026 11:46:31 +0000
Subject: [PATCH 1/7] Add OVPhysX presets to the dexterous tasks

The Shadow Hand reorientation and handover environments gain OVPhysX
physics presets (spawned without fixed-tendon overrides, which the
OVPhysX runtime does not expose), and the Shadow Hand task frame is
corrected on OVPhysX.

Validated by full training runs on the OVPhysX backend.
---
 .../task-cleanup-dex-part07.minor.rst         | 10 ++
 .../core/handover/handover_env_cfg.py         | 29 ++++--
 .../config/shadow_hand/shadow_hand_env_cfg.py | 12 +++
 .../core/test_dexterous_ovphysx_presets.py    | 96 +++++++++++++++++++
 .../test/core/test_handover_env_cfg.py        | 51 ++++++++++
 .../test/core/test_shadow_hand_env_cfg.py     | 80 ++++++++++++++++
 6 files changed, 268 insertions(+), 10 deletions(-)
 create mode 100644 source/isaaclab_tasks/changelog.d/task-cleanup-dex-part07.minor.rst
 create mode 100644 source/isaaclab_tasks/test/core/test_dexterous_ovphysx_presets.py
 create mode 100644 source/isaaclab_tasks/test/core/test_handover_env_cfg.py
 create mode 100644 source/isaaclab_tasks/test/core/test_shadow_hand_env_cfg.py

diff --git a/source/isaaclab_tasks/changelog.d/task-cleanup-dex-part07.minor.rst b/source/isaaclab_tasks/changelog.d/task-cleanup-dex-part07.minor.rst
new file mode 100644
index 000000000000..ecbf7abb40d7
--- /dev/null
+++ b/source/isaaclab_tasks/changelog.d/task-cleanup-dex-part07.minor.rst
@@ -0,0 +1,10 @@
+Added
+^^^^^
+
+* Added OVPhysX physics presets to the Shadow Hand reorientation and handover
+  environments.
+
+Fixed
+^^^^^
+
+* Fixed the Shadow Hand task frame on OVPhysX.
diff --git a/source/isaaclab_tasks/isaaclab_tasks/core/handover/handover_env_cfg.py b/source/isaaclab_tasks/isaaclab_tasks/core/handover/handover_env_cfg.py
index a3d7126ce0bd..9fc81cf0af0d 100644
--- a/source/isaaclab_tasks/isaaclab_tasks/core/handover/handover_env_cfg.py
+++ b/source/isaaclab_tasks/isaaclab_tasks/core/handover/handover_env_cfg.py
@@ -4,6 +4,7 @@
 # SPDX-License-Identifier: BSD-3-Clause
 
 from isaaclab_newton.physics import MJWarpSolverCfg, NewtonCfg
+from isaaclab_ovphysx.physics import OvPhysxCfg
 from isaaclab_physx.physics import PhysxCfg
 
 import isaaclab.envs.mdp as mdp
@@ -136,9 +137,9 @@ def _shadow_hand_cfg(
     init_pos: tuple[float, float, float],
     init_rot: tuple[float, float, float, float],
 ) -> PresetCfg:
-    """Per-hand Shadow Hand preset (PhysX and Newton MJWarp variants).
+    """Per-hand Shadow Hand preset (PhysX, Newton MJWarp, and OVPhysX variants).
 
-    Both variants are placed at *prim_path* with the same init pose; per-hand
+    All variants are placed at *prim_path* with the same init pose; per-hand
     differences (right vs left) come from the caller's *prim_path* / *init_pos* /
     *init_rot* — the gain tuning is identical on both hands.
 
@@ -154,12 +155,13 @@ def _shadow_hand_cfg(
       authority. ``20.0`` / ``2.0`` is the smallest tested setting at which
       MAPPO learns the catch (mean reward at iter 200 / 2048 envs goes from
       ~27 at PhysX-mirrored gains to ~777).
-    * ``distal_passive`` on the four ``robot0_(FF|MF|RF|LF)J0`` joints with
-      ``stiffness=10.0`` / ``damping=0.1``. The Newton USD bakes
-      ``stiffness=286 / damping=57`` on these joints from the MJCF→USD
-      translation, which fights the ``MjcTendon`` coupling and bounces the
-      ball. ``stiffness=10`` (~1/3 of PhysX's ``limit_stiffness=30``) keeps
-      the joints near-passive while the tendon constraint dominates.
+    * ``distal_passive`` on the four ``robot0_(FF|MF|RF|LF)J1`` distal joints
+      (named ``J0`` before the current asset release) with ``stiffness=10.0`` /
+      ``damping=0.1``. The Newton USD bakes ``stiffness=286 / damping=57`` on
+      these joints from the MJCF→USD translation, which fights the
+      ``MjcTendon`` coupling and bounces the ball. ``stiffness=10`` (~1/3 of
+      PhysX's ``limit_stiffness=30``) keeps the joints near-passive while the
+      tendon constraint dominates.
     """
     physx_cfg = SHADOW_HAND_CFG.replace(prim_path=prim_path).replace(
         init_state=ArticulationCfg.InitialStateCfg(pos=init_pos, rot=init_rot, joint_pos={".*": 0.0})
@@ -170,7 +172,7 @@ def _shadow_hand_cfg(
         actuators={
             "fingers": _SHADOW_HAND_NEWTON_CFG.actuators["fingers"].replace(stiffness=20.0, damping=2.0),
             "distal_passive": ImplicitActuatorCfg(
-                joint_names_expr=["robot0_(FF|MF|RF|LF)J0"],
+                joint_names_expr=["robot0_(FF|MF|RF|LF)J1"],
                 stiffness=10.0,
                 damping=0.1,
                 friction=1e-2,
@@ -178,7 +180,13 @@ def _shadow_hand_cfg(
             ),
         },
     )
-    return preset(default=physx_cfg, physx=physx_cfg, newton_mjwarp=newton_cfg)
+    ovphysx_cfg = SHADOW_HAND_CFG.replace(
+        prim_path=prim_path,
+        # OVPhysX does not expose the fixed-tendon runtime API, so spawn without tendon overrides.
+        spawn=SHADOW_HAND_CFG.spawn.replace(fixed_tendons_props=None),
+        init_state=SHADOW_HAND_CFG.init_state.replace(pos=init_pos, rot=init_rot),
+    )
+    return preset(default=physx_cfg, physx=physx_cfg, newton_mjwarp=newton_cfg, ovphysx=ovphysx_cfg)
 
 
 @configclass
@@ -261,6 +269,7 @@ class PhysicsCfg(PresetCfg):
         num_substeps=2,
         debug_mode=False,
     )
+    ovphysx = OvPhysxCfg()
     default = physx
 
 
diff --git a/source/isaaclab_tasks/isaaclab_tasks/core/reorient/config/shadow_hand/shadow_hand_env_cfg.py b/source/isaaclab_tasks/isaaclab_tasks/core/reorient/config/shadow_hand/shadow_hand_env_cfg.py
index f6bdae2bd0d8..732f3805a3f5 100644
--- a/source/isaaclab_tasks/isaaclab_tasks/core/reorient/config/shadow_hand/shadow_hand_env_cfg.py
+++ b/source/isaaclab_tasks/isaaclab_tasks/core/reorient/config/shadow_hand/shadow_hand_env_cfg.py
@@ -4,6 +4,7 @@
 # SPDX-License-Identifier: BSD-3-Clause
 
 from isaaclab_newton.physics import KaminoSolverCfg, MJWarpSolverCfg, NewtonCfg
+from isaaclab_ovphysx.physics import OvPhysxCfg
 from isaaclab_physx.physics import PhysxCfg
 
 import isaaclab.envs.mdp as mdp
@@ -207,6 +208,16 @@ class ShadowHandRobotCfg(PresetCfg):
         },
         soft_joint_pos_limit_factor=1.0,
     )
+    ovphysx = SHADOW_HAND_CFG.replace(
+        prim_path="/World/envs/env_.*/Robot",
+        # OVPhysX does not expose the fixed-tendon runtime API, so spawn without tendon overrides.
+        spawn=SHADOW_HAND_CFG.spawn.replace(fixed_tendons_props=None),
+        init_state=ArticulationCfg.InitialStateCfg(
+            pos=(0.0, 0.0, 0.5),
+            rot=(0.0, 0.0, 0.0, 1.0),
+            joint_pos={".*": 0.0},
+        ),
+    )
     default = physx
     newton_kamino = newton_mjwarp
 
@@ -290,6 +301,7 @@ class PhysicsCfg(PresetCfg):
         num_substeps=2,
         debug_mode=False,
     )
+    ovphysx = OvPhysxCfg()
     default = physx
     newton_kamino = NewtonCfg(solver_cfg=KaminoSolverCfg(max_contacts_per_world=128))
 
diff --git a/source/isaaclab_tasks/test/core/test_dexterous_ovphysx_presets.py b/source/isaaclab_tasks/test/core/test_dexterous_ovphysx_presets.py
new file mode 100644
index 000000000000..982a5813a011
--- /dev/null
+++ b/source/isaaclab_tasks/test/core/test_dexterous_ovphysx_presets.py
@@ -0,0 +1,96 @@
+# Copyright (c) 2022-2026, The Isaac Lab Project Developers (https://github.com/isaac-sim/IsaacLab/blob/main/CONTRIBUTORS.md).
+# All rights reserved.
+#
+# SPDX-License-Identifier: BSD-3-Clause
+
+"""Configuration tests for OVPhysX support in assigned dexterous tasks."""
+
+import pytest
+from isaaclab_newton.physics import NewtonCfg
+from isaaclab_ovphysx.physics import OvPhysxCfg
+
+from isaaclab.assets import ArticulationCfg
+
+from isaaclab_tasks.core.handover.handover_env_cfg import HandoverEnvCfg
+from isaaclab_tasks.core.handover.handover_manager_env_cfg import HandoverManagerEnvCfg
+from isaaclab_tasks.core.reorient.config.allegro_hand.allegro_hand_direct_env_cfg import AllegroHandEnvCfg
+from isaaclab_tasks.core.reorient.config.allegro_hand.allegro_hand_manager_env_cfg import (
+    AllegroCubeEnvCfg,
+    AllegroCubeEnvCfg_PLAY,
+)
+from isaaclab_tasks.core.reorient.config.shadow_hand.shadow_hand_camera_env_cfg import (
+    ShadowHandCameraBenchmarkEnvCfg,
+    ShadowHandCameraEnvCfg,
+    ShadowHandCameraEnvPlayCfg,
+)
+from isaaclab_tasks.core.reorient.config.shadow_hand.shadow_hand_camera_manager_env_cfg import (
+    ShadowHandCameraManagerBenchmarkEnvCfg,
+    ShadowHandCameraManagerEnvCfg,
+    ShadowHandCameraManagerPlayEnvCfg,
+)
+from isaaclab_tasks.core.reorient.config.shadow_hand.shadow_hand_env_cfg import (
+    ShadowHandEnvCfg,
+    ShadowHandOpenAIEnvCfg,
+)
+from isaaclab_tasks.core.reorient.config.shadow_hand.shadow_hand_manager_env_cfg import (
+    ShadowHandManagerEnvCfg,
+    ShadowHandOpenAIManagerEnvCfg,
+)
+from isaaclab_tasks.utils.hydra import collect_presets, resolve_presets
+
+
+@pytest.mark.parametrize(
+    "env_cfg_type",
+    [
+        pytest.param(AllegroHandEnvCfg, id="allegro_direct"),
+        pytest.param(ShadowHandEnvCfg, id="shadow_direct"),
+        pytest.param(ShadowHandOpenAIEnvCfg, id="shadow_openai_ff"),
+        pytest.param(ShadowHandCameraEnvCfg, id="shadow_camera"),
+        pytest.param(ShadowHandCameraEnvPlayCfg, id="shadow_camera_play"),
+        pytest.param(ShadowHandCameraBenchmarkEnvCfg, id="shadow_camera_benchmark"),
+        pytest.param(ShadowHandCameraManagerEnvCfg, id="shadow_camera_manager"),
+        pytest.param(ShadowHandCameraManagerPlayEnvCfg, id="shadow_camera_manager_play"),
+        pytest.param(ShadowHandCameraManagerBenchmarkEnvCfg, id="shadow_camera_manager_benchmark"),
+        pytest.param(HandoverEnvCfg, id="handover"),
+        pytest.param(HandoverManagerEnvCfg, id="handover_manager"),
+        pytest.param(AllegroCubeEnvCfg, id="allegro_manager"),
+        pytest.param(AllegroCubeEnvCfg_PLAY, id="allegro_manager_play"),
+        pytest.param(ShadowHandManagerEnvCfg, id="shadow_manager"),
+        pytest.param(ShadowHandOpenAIManagerEnvCfg, id="shadow_openai_manager"),
+    ],
+)
+def test_ovphysx_physics_preset_resolves_for_assigned_dexterous_variants(env_cfg_type):
+    """Verify every assigned variant resolves its physics preset to OVPhysX."""
+    env_cfg = env_cfg_type()
+
+    assert "ovphysx" in collect_presets(env_cfg)["sim.physics"]
+
+    resolved_cfg = resolve_presets(env_cfg, {"ovphysx"})
+
+    assert isinstance(resolved_cfg.sim.physics, OvPhysxCfg)
+
+
+@pytest.mark.parametrize("env_cfg_type", [AllegroCubeEnvCfg, AllegroCubeEnvCfg_PLAY])
+def test_newton_physics_and_scene_presets_resolve_for_allegro_manager(env_cfg_type):
+    """Verify Allegro Manager uses Newton physics, an articulated cube, and non-Fabric cloning."""
+    resolved_cfg = resolve_presets(env_cfg_type(), {"newton_mjwarp"})
+
+    assert isinstance(resolved_cfg.sim.physics, NewtonCfg)
+    assert isinstance(resolved_cfg.scene.object, ArticulationCfg)
+    assert not resolved_cfg.scene.clone_in_fabric
+
+
+@pytest.mark.parametrize("env_cfg_type", [HandoverEnvCfg, HandoverManagerEnvCfg])
+def test_newton_physics_and_scene_presets_resolve_for_handover(env_cfg_type):
+    """Verify Direct and Manager Handover resolve Newton physics and cloning together."""
+    resolved_cfg = resolve_presets(env_cfg_type(), {"newton_mjwarp"})
+
+    assert isinstance(resolved_cfg.sim.physics, NewtonCfg)
+    assert not resolved_cfg.scene.clone_in_fabric
+
+
+def test_default_physics_scene_preset_resolves_play_env_count_for_allegro_manager():
+    """Verify the default Allegro Manager play scene retains its reduced environment count."""
+    resolved_cfg = resolve_presets(AllegroCubeEnvCfg_PLAY(), set())
+
+    assert resolved_cfg.scene.num_envs == 50
diff --git a/source/isaaclab_tasks/test/core/test_handover_env_cfg.py b/source/isaaclab_tasks/test/core/test_handover_env_cfg.py
new file mode 100644
index 000000000000..487cb110111d
--- /dev/null
+++ b/source/isaaclab_tasks/test/core/test_handover_env_cfg.py
@@ -0,0 +1,51 @@
+# Copyright (c) 2022-2026, The Isaac Lab Project Developers (https://github.com/isaac-sim/IsaacLab/blob/main/CONTRIBUTORS.md).
+# All rights reserved.
+#
+# SPDX-License-Identifier: BSD-3-Clause
+
+"""Tests for the Shadow Hand handover environment configuration."""
+
+import pytest
+
+from isaaclab_tasks.core.handover.handover_env_cfg import HandoverEnvCfg
+from isaaclab_tasks.core.handover.handover_manager_env_cfg import HandoverManagerEnvCfg
+from isaaclab_tasks.core.reorient.config.shadow_hand.shadow_hand_env_cfg import ShadowHandEnvCfg
+
+
+def test_hands_use_standard_shadow_assets():
+    """Verify both hands reuse the single-agent Shadow Hand assets per backend."""
+    cfg = HandoverEnvCfg()
+    single_agent_robot_cfg = ShadowHandEnvCfg().robot_cfg
+
+    for hand in (cfg.right_robot_cfg, cfg.left_robot_cfg):
+        assert hand.physx.spawn.usd_path == single_agent_robot_cfg.physx.spawn.usd_path
+        assert hand.newton_mjwarp.spawn.usd_path == single_agent_robot_cfg.newton_mjwarp.spawn.usd_path
+        assert hand.ovphysx.spawn.usd_path == single_agent_robot_cfg.ovphysx.spawn.usd_path
+        assert hand.newton_mjwarp.spawn.fixed_tendons_props.damping == 0.1
+
+
+def test_hands_place_each_backend_with_the_same_pose():
+    """Verify each hand uses one init pose across backends and normalized rotations."""
+    cfg = HandoverEnvCfg()
+
+    for hand in (cfg.right_robot_cfg, cfg.left_robot_cfg):
+        assert hand.newton_mjwarp.init_state.pos == hand.physx.init_state.pos == hand.ovphysx.init_state.pos
+        assert hand.physx.init_state.rot == hand.ovphysx.init_state.rot
+        assert sum(value**2 for value in hand.newton_mjwarp.init_state.rot) == pytest.approx(1.0)
+
+    assert cfg.right_robot_cfg.physx.init_state.rot == (0.0, 0.0, 0.0, 1.0)
+    assert cfg.left_robot_cfg.physx.init_state.rot == (0.0, 0.0, 1.0, 0.0)
+
+    manager_cfg = HandoverManagerEnvCfg()
+    manager_scene = manager_cfg.scene.newton_mjwarp
+    assert manager_scene.right_hand.newton_mjwarp.init_state.rot == cfg.right_robot_cfg.newton_mjwarp.init_state.rot
+    assert manager_scene.left_hand.newton_mjwarp.init_state.rot == cfg.left_robot_cfg.newton_mjwarp.init_state.rot
+
+
+def test_newton_hands_override_passive_distal_joints():
+    """Verify Newton hands keep the near-passive distal-joint override."""
+    cfg = HandoverEnvCfg()
+
+    for hand in (cfg.right_robot_cfg, cfg.left_robot_cfg):
+        assert set(hand.newton_mjwarp.actuators) == {"fingers", "distal_passive"}
+        assert hand.newton_mjwarp.actuators["distal_passive"].stiffness == 10.0
diff --git a/source/isaaclab_tasks/test/core/test_shadow_hand_env_cfg.py b/source/isaaclab_tasks/test/core/test_shadow_hand_env_cfg.py
new file mode 100644
index 000000000000..beb68d7a81f3
--- /dev/null
+++ b/source/isaaclab_tasks/test/core/test_shadow_hand_env_cfg.py
@@ -0,0 +1,80 @@
+# Copyright (c) 2022-2026, The Isaac Lab Project Developers (https://github.com/isaac-sim/IsaacLab/blob/main/CONTRIBUTORS.md).
+# All rights reserved.
+#
+# SPDX-License-Identifier: BSD-3-Clause
+
+"""Tests for the shared Shadow Hand environment configuration."""
+
+import pytest
+
+from isaaclab.utils.assets import ISAAC_NUCLEUS_DIR
+
+from isaaclab_tasks.core.reorient.config.shadow_hand.shadow_hand_env_cfg import (
+    NewtonEventCfg,
+    PhysxEventCfg,
+    ShadowHandEnvCfg,
+)
+
+from isaaclab_assets import SHADOW_HAND_CFG
+
+
+def test_events_randomize_fixed_tendons_on_both_backends():
+    """Verify PhysX and Newton events preserve fixed-tendon randomization."""
+    for event_cfg in (PhysxEventCfg(), NewtonEventCfg()):
+        event = event_cfg.robot_tendon_properties
+
+        assert event.func.__name__ == "randomize_fixed_tendon_parameters"
+        assert event.params["asset_cfg"].fixed_tendon_names == ".*"
+
+
+def test_shadow_variants_use_supported_asset_and_backend_physics_layers():
+    """Verify each backend preset uses the production Shadow Hand asset it supports."""
+    cfg = ShadowHandEnvCfg()
+    legacy_path = f"{ISAAC_NUCLEUS_DIR}/Robots/ShadowRobot/ShadowHand/shadow_hand_instanceable.usd"
+
+    assert SHADOW_HAND_CFG.spawn.usd_path == legacy_path
+    assert SHADOW_HAND_CFG.spawn.fixed_tendons_props is not None
+    assert cfg.robot_cfg.physx.spawn.usd_path == legacy_path
+    assert cfg.robot_cfg.ovphysx.spawn.usd_path == legacy_path
+    assert cfg.robot_cfg.newton_mjwarp.spawn.usd_path == (
+        f"{ISAAC_NUCLEUS_DIR}/Robots/ShadowRobot/ShadowHandNewton/shadow_hand_instanceable.usda"
+    )
+    assert cfg.robot_cfg.physx.spawn.variants is None
+    assert cfg.robot_cfg.ovphysx.spawn.variants is None
+    assert cfg.robot_cfg.newton_mjwarp.spawn.variants is None
+    assert cfg.robot_cfg.ovphysx.spawn.fixed_tendons_props is None
+    assert cfg.robot_cfg.physx.init_state.rot == (0.0, 0.0, 0.0, 1.0)
+    assert cfg.robot_cfg.ovphysx.init_state.rot == (0.0, 0.0, 0.0, 1.0)
+    assert cfg.robot_cfg.newton_mjwarp.spawn.fixed_tendons_props.damping == 0.1
+    assert cfg.robot_cfg.newton_mjwarp.init_state.rot == (0.0, 0.0, -0.70710678118, 0.70710678118)
+    assert sum(value**2 for value in cfg.robot_cfg.newton_mjwarp.init_state.rot) == pytest.approx(1.0)
+    assert cfg.sim.physics.newton_mjwarp.num_substeps == 2
+
+
+def test_shadow_joint_mapping_preserves_twenty_action_contract():
+    """Verify the actuated-joint list preserves the legacy 20-action order."""
+    cfg = ShadowHandEnvCfg()
+
+    assert cfg.action_space == len(cfg.actuated_joint_names) == 20
+    assert cfg.actuated_joint_names == [
+        "robot0_WRJ1",
+        "robot0_WRJ0",
+        "robot0_FFJ3",
+        "robot0_FFJ2",
+        "robot0_FFJ1",
+        "robot0_MFJ3",
+        "robot0_MFJ2",
+        "robot0_MFJ1",
+        "robot0_RFJ3",
+        "robot0_RFJ2",
+        "robot0_RFJ1",
+        "robot0_LFJ4",
+        "robot0_LFJ3",
+        "robot0_LFJ2",
+        "robot0_LFJ1",
+        "robot0_THJ4",
+        "robot0_THJ3",
+        "robot0_THJ2",
+        "robot0_THJ1",
+        "robot0_THJ0",
+    ]

From 770cb46fd835d1b7d520a2ace42200835e9c8fe9 Mon Sep 17 00:00:00 2001
From: jichuanh <jichuanh@nvidia.com>
Date: Wed, 8 Jul 2026 12:57:24 +0000
Subject: [PATCH 2/7] Restrict the acceptance tests to the Direct variants

The earlier commit was meant to ship the reduced Direct-only test set
but the reduction was accidentally committed on a detached HEAD and
never reached the branch. The manager-importing test rows and the
handover configuration test move to the final manager PR, which is
where their imports resolve.
---
 .../core/test_dexterous_ovphysx_presets.py    | 53 +------------------
 .../test/core/test_handover_env_cfg.py        | 51 ------------------
 2 files changed, 2 insertions(+), 102 deletions(-)
 delete mode 100644 source/isaaclab_tasks/test/core/test_handover_env_cfg.py

diff --git a/source/isaaclab_tasks/test/core/test_dexterous_ovphysx_presets.py b/source/isaaclab_tasks/test/core/test_dexterous_ovphysx_presets.py
index 982a5813a011..0c4bb125093e 100644
--- a/source/isaaclab_tasks/test/core/test_dexterous_ovphysx_presets.py
+++ b/source/isaaclab_tasks/test/core/test_dexterous_ovphysx_presets.py
@@ -9,33 +9,12 @@
 from isaaclab_newton.physics import NewtonCfg
 from isaaclab_ovphysx.physics import OvPhysxCfg
 
-from isaaclab.assets import ArticulationCfg
-
 from isaaclab_tasks.core.handover.handover_env_cfg import HandoverEnvCfg
-from isaaclab_tasks.core.handover.handover_manager_env_cfg import HandoverManagerEnvCfg
 from isaaclab_tasks.core.reorient.config.allegro_hand.allegro_hand_direct_env_cfg import AllegroHandEnvCfg
-from isaaclab_tasks.core.reorient.config.allegro_hand.allegro_hand_manager_env_cfg import (
-    AllegroCubeEnvCfg,
-    AllegroCubeEnvCfg_PLAY,
-)
-from isaaclab_tasks.core.reorient.config.shadow_hand.shadow_hand_camera_env_cfg import (
-    ShadowHandCameraBenchmarkEnvCfg,
-    ShadowHandCameraEnvCfg,
-    ShadowHandCameraEnvPlayCfg,
-)
-from isaaclab_tasks.core.reorient.config.shadow_hand.shadow_hand_camera_manager_env_cfg import (
-    ShadowHandCameraManagerBenchmarkEnvCfg,
-    ShadowHandCameraManagerEnvCfg,
-    ShadowHandCameraManagerPlayEnvCfg,
-)
 from isaaclab_tasks.core.reorient.config.shadow_hand.shadow_hand_env_cfg import (
     ShadowHandEnvCfg,
     ShadowHandOpenAIEnvCfg,
 )
-from isaaclab_tasks.core.reorient.config.shadow_hand.shadow_hand_manager_env_cfg import (
-    ShadowHandManagerEnvCfg,
-    ShadowHandOpenAIManagerEnvCfg,
-)
 from isaaclab_tasks.utils.hydra import collect_presets, resolve_presets
 
 
@@ -45,18 +24,7 @@
         pytest.param(AllegroHandEnvCfg, id="allegro_direct"),
         pytest.param(ShadowHandEnvCfg, id="shadow_direct"),
         pytest.param(ShadowHandOpenAIEnvCfg, id="shadow_openai_ff"),
-        pytest.param(ShadowHandCameraEnvCfg, id="shadow_camera"),
-        pytest.param(ShadowHandCameraEnvPlayCfg, id="shadow_camera_play"),
-        pytest.param(ShadowHandCameraBenchmarkEnvCfg, id="shadow_camera_benchmark"),
-        pytest.param(ShadowHandCameraManagerEnvCfg, id="shadow_camera_manager"),
-        pytest.param(ShadowHandCameraManagerPlayEnvCfg, id="shadow_camera_manager_play"),
-        pytest.param(ShadowHandCameraManagerBenchmarkEnvCfg, id="shadow_camera_manager_benchmark"),
         pytest.param(HandoverEnvCfg, id="handover"),
-        pytest.param(HandoverManagerEnvCfg, id="handover_manager"),
-        pytest.param(AllegroCubeEnvCfg, id="allegro_manager"),
-        pytest.param(AllegroCubeEnvCfg_PLAY, id="allegro_manager_play"),
-        pytest.param(ShadowHandManagerEnvCfg, id="shadow_manager"),
-        pytest.param(ShadowHandOpenAIManagerEnvCfg, id="shadow_openai_manager"),
     ],
 )
 def test_ovphysx_physics_preset_resolves_for_assigned_dexterous_variants(env_cfg_type):
@@ -70,27 +38,10 @@ def test_ovphysx_physics_preset_resolves_for_assigned_dexterous_variants(env_cfg
     assert isinstance(resolved_cfg.sim.physics, OvPhysxCfg)
 
 
-@pytest.mark.parametrize("env_cfg_type", [AllegroCubeEnvCfg, AllegroCubeEnvCfg_PLAY])
-def test_newton_physics_and_scene_presets_resolve_for_allegro_manager(env_cfg_type):
-    """Verify Allegro Manager uses Newton physics, an articulated cube, and non-Fabric cloning."""
-    resolved_cfg = resolve_presets(env_cfg_type(), {"newton_mjwarp"})
-
-    assert isinstance(resolved_cfg.sim.physics, NewtonCfg)
-    assert isinstance(resolved_cfg.scene.object, ArticulationCfg)
-    assert not resolved_cfg.scene.clone_in_fabric
-
-
-@pytest.mark.parametrize("env_cfg_type", [HandoverEnvCfg, HandoverManagerEnvCfg])
+@pytest.mark.parametrize("env_cfg_type", [HandoverEnvCfg])
 def test_newton_physics_and_scene_presets_resolve_for_handover(env_cfg_type):
-    """Verify Direct and Manager Handover resolve Newton physics and cloning together."""
+    """Verify Direct Handover resolves Newton physics and cloning together."""
     resolved_cfg = resolve_presets(env_cfg_type(), {"newton_mjwarp"})
 
     assert isinstance(resolved_cfg.sim.physics, NewtonCfg)
     assert not resolved_cfg.scene.clone_in_fabric
-
-
-def test_default_physics_scene_preset_resolves_play_env_count_for_allegro_manager():
-    """Verify the default Allegro Manager play scene retains its reduced environment count."""
-    resolved_cfg = resolve_presets(AllegroCubeEnvCfg_PLAY(), set())
-
-    assert resolved_cfg.scene.num_envs == 50
diff --git a/source/isaaclab_tasks/test/core/test_handover_env_cfg.py b/source/isaaclab_tasks/test/core/test_handover_env_cfg.py
deleted file mode 100644
index 487cb110111d..000000000000
--- a/source/isaaclab_tasks/test/core/test_handover_env_cfg.py
+++ /dev/null
@@ -1,51 +0,0 @@
-# Copyright (c) 2022-2026, The Isaac Lab Project Developers (https://github.com/isaac-sim/IsaacLab/blob/main/CONTRIBUTORS.md).
-# All rights reserved.
-#
-# SPDX-License-Identifier: BSD-3-Clause
-
-"""Tests for the Shadow Hand handover environment configuration."""
-
-import pytest
-
-from isaaclab_tasks.core.handover.handover_env_cfg import HandoverEnvCfg
-from isaaclab_tasks.core.handover.handover_manager_env_cfg import HandoverManagerEnvCfg
-from isaaclab_tasks.core.reorient.config.shadow_hand.shadow_hand_env_cfg import ShadowHandEnvCfg
-
-
-def test_hands_use_standard_shadow_assets():
-    """Verify both hands reuse the single-agent Shadow Hand assets per backend."""
-    cfg = HandoverEnvCfg()
-    single_agent_robot_cfg = ShadowHandEnvCfg().robot_cfg
-
-    for hand in (cfg.right_robot_cfg, cfg.left_robot_cfg):
-        assert hand.physx.spawn.usd_path == single_agent_robot_cfg.physx.spawn.usd_path
-        assert hand.newton_mjwarp.spawn.usd_path == single_agent_robot_cfg.newton_mjwarp.spawn.usd_path
-        assert hand.ovphysx.spawn.usd_path == single_agent_robot_cfg.ovphysx.spawn.usd_path
-        assert hand.newton_mjwarp.spawn.fixed_tendons_props.damping == 0.1
-
-
-def test_hands_place_each_backend_with_the_same_pose():
-    """Verify each hand uses one init pose across backends and normalized rotations."""
-    cfg = HandoverEnvCfg()
-
-    for hand in (cfg.right_robot_cfg, cfg.left_robot_cfg):
-        assert hand.newton_mjwarp.init_state.pos == hand.physx.init_state.pos == hand.ovphysx.init_state.pos
-        assert hand.physx.init_state.rot == hand.ovphysx.init_state.rot
-        assert sum(value**2 for value in hand.newton_mjwarp.init_state.rot) == pytest.approx(1.0)
-
-    assert cfg.right_robot_cfg.physx.init_state.rot == (0.0, 0.0, 0.0, 1.0)
-    assert cfg.left_robot_cfg.physx.init_state.rot == (0.0, 0.0, 1.0, 0.0)
-
-    manager_cfg = HandoverManagerEnvCfg()
-    manager_scene = manager_cfg.scene.newton_mjwarp
-    assert manager_scene.right_hand.newton_mjwarp.init_state.rot == cfg.right_robot_cfg.newton_mjwarp.init_state.rot
-    assert manager_scene.left_hand.newton_mjwarp.init_state.rot == cfg.left_robot_cfg.newton_mjwarp.init_state.rot
-
-
-def test_newton_hands_override_passive_distal_joints():
-    """Verify Newton hands keep the near-passive distal-joint override."""
-    cfg = HandoverEnvCfg()
-
-    for hand in (cfg.right_robot_cfg, cfg.left_robot_cfg):
-        assert set(hand.newton_mjwarp.actuators) == {"fingers", "distal_passive"}
-        assert hand.newton_mjwarp.actuators["distal_passive"].stiffness == 10.0

From 935284ed80ece8ed85a4aea5ab95c125b206ad08 Mon Sep 17 00:00:00 2001
From: jichuanh <jichuanh@nvidia.com>
Date: Thu, 9 Jul 2026 01:05:40 +0000
Subject: [PATCH 3/7] Carry the handover Newton fixes in the full backend
 preset

Mirrors the per-backend actuated-joint mapping, composed hand
rotations, and contact substeps shipped in the handover enablement PR;
this file remains the superset with the OVPhysX preset.
---
 .../core/handover/handover_env_cfg.py         | 135 ++++++++++++++----
 1 file changed, 110 insertions(+), 25 deletions(-)

diff --git a/source/isaaclab_tasks/isaaclab_tasks/core/handover/handover_env_cfg.py b/source/isaaclab_tasks/isaaclab_tasks/core/handover/handover_env_cfg.py
index 9fc81cf0af0d..9b72c38ebc4b 100644
--- a/source/isaaclab_tasks/isaaclab_tasks/core/handover/handover_env_cfg.py
+++ b/source/isaaclab_tasks/isaaclab_tasks/core/handover/handover_env_cfg.py
@@ -132,6 +132,71 @@ class EventCfg:
 _SHADOW_HAND_NEWTON_CFG = ShadowHandRobotCfg().newton_mjwarp
 
 
+# Physical actuated set of the Shadow Hand (wrist + non-distal finger joints +
+# full thumb). The PhysX and OVPhysX asset names the finger chains J0..J3
+# (LF: J0..J4) with the tendon-coupled distal pair unactuated; the production
+# Newton asset renumbers the four finger chains by +1 (FF/MF/RF: J1..J4,
+# LF: J1..J5, distal = J1), so the same physical joints carry shifted names.
+_ACTUATED_JOINT_NAMES = [
+    "robot0_WRJ1",
+    "robot0_WRJ0",
+    "robot0_FFJ3",
+    "robot0_FFJ2",
+    "robot0_FFJ1",
+    "robot0_MFJ3",
+    "robot0_MFJ2",
+    "robot0_MFJ1",
+    "robot0_RFJ3",
+    "robot0_RFJ2",
+    "robot0_RFJ1",
+    "robot0_LFJ4",
+    "robot0_LFJ3",
+    "robot0_LFJ2",
+    "robot0_LFJ1",
+    "robot0_THJ4",
+    "robot0_THJ3",
+    "robot0_THJ2",
+    "robot0_THJ1",
+    "robot0_THJ0",
+]
+_ACTUATED_JOINT_NAMES_NEWTON = [
+    "robot0_WRJ1",
+    "robot0_WRJ0",
+    "robot0_FFJ4",
+    "robot0_FFJ3",
+    "robot0_FFJ2",
+    "robot0_MFJ4",
+    "robot0_MFJ3",
+    "robot0_MFJ2",
+    "robot0_RFJ4",
+    "robot0_RFJ3",
+    "robot0_RFJ2",
+    "robot0_LFJ5",
+    "robot0_LFJ4",
+    "robot0_LFJ3",
+    "robot0_LFJ2",
+    "robot0_THJ4",
+    "robot0_THJ3",
+    "robot0_THJ2",
+    "robot0_THJ1",
+    "robot0_THJ0",
+]
+
+
+def _quat_mul_xyzw(
+    q1: tuple[float, float, float, float], q2: tuple[float, float, float, float]
+) -> tuple[float, float, float, float]:
+    """Compose two ``(x, y, z, w)`` quaternions (``q1`` applied on top of ``q2``)."""
+    x1, y1, z1, w1 = q1
+    x2, y2, z2, w2 = q2
+    return (
+        w1 * x2 + x1 * w2 + y1 * z2 - z1 * y2,
+        w1 * y2 - x1 * z2 + y1 * w2 + z1 * x2,
+        w1 * z2 + x1 * y2 - y1 * x2 + z1 * w2,
+        w1 * w2 - x1 * x2 - y1 * y2 - z1 * z2,
+    )
+
+
 def _shadow_hand_cfg(
     prim_path: str,
     init_pos: tuple[float, float, float],
@@ -166,11 +231,44 @@ def _shadow_hand_cfg(
     physx_cfg = SHADOW_HAND_CFG.replace(prim_path=prim_path).replace(
         init_state=ArticulationCfg.InitialStateCfg(pos=init_pos, rot=init_rot, joint_pos={".*": 0.0})
     )
+    # Newton's importer bakes the asset's native root orientation into the
+    # root joint (see the note on _SHADOW_HAND_NEWTON_CFG.init_state), so the
+    # task rotation must compose with that base rotation rather than replace
+    # it — replacing left both palms heading 90 degrees off and the object
+    # never rested in the right hand.
+    newton_rot = _quat_mul_xyzw(init_rot, _SHADOW_HAND_NEWTON_CFG.init_state.rot)
     newton_cfg = _SHADOW_HAND_NEWTON_CFG.replace(
         prim_path=prim_path,
-        init_state=_SHADOW_HAND_NEWTON_CFG.init_state.replace(pos=init_pos, rot=init_rot),
+        init_state=_SHADOW_HAND_NEWTON_CFG.init_state.replace(pos=init_pos, rot=newton_rot),
         actuators={
-            "fingers": _SHADOW_HAND_NEWTON_CFG.actuators["fingers"].replace(stiffness=20.0, damping=2.0),
+            # The inherited "fingers" expression predates the renamed Newton
+            # asset: on the renumbered chains it drives the tendon-coupled
+            # distal J1 joints and leaves the J4 knuckles (and the LFJ5
+            # metacarpal) without a drive. Redeclare it against the renamed
+            # joints so the actuated set matches the PhysX hand physically.
+            "fingers": _SHADOW_HAND_NEWTON_CFG.actuators["fingers"].replace(
+                joint_names_expr=[
+                    "robot0_WR.*",
+                    "robot0_(FF|MF|RF)J(4|3|2)",
+                    "robot0_LFJ(5|4|3|2)",
+                    "robot0_THJ[0-4]",
+                ],
+                effort_limit_sim={
+                    "robot0_WRJ1": 4.785,
+                    "robot0_WRJ0": 2.175,
+                    "robot0_(FF|MF|RF|LF)J2": 0.7245,
+                    "robot0_FFJ(4|3)": 0.9,
+                    "robot0_MFJ(4|3)": 0.9,
+                    "robot0_RFJ(4|3)": 0.9,
+                    "robot0_LFJ(5|4|3)": 0.9,
+                    "robot0_THJ4": 2.3722,
+                    "robot0_THJ3": 1.45,
+                    "robot0_THJ(2|1)": 0.99,
+                    "robot0_THJ0": 0.81,
+                },
+                stiffness=20.0,
+                damping=2.0,
+            ),
             "distal_passive": ImplicitActuatorCfg(
                 joint_names_expr=["robot0_(FF|MF|RF|LF)J1"],
                 stiffness=10.0,
@@ -266,7 +364,10 @@ class PhysicsCfg(PresetCfg):
             update_data_interval=2,
             ccd_iterations=50,  # bumped from default 35 for multi-finger contact geometry
         ),
-        num_substeps=2,
+        # 4 substeps (vs the single-agent port's 2): sustained ball-palm contact
+        # against the near-passive distal joints explodes ~0.7% of 8192 envs to
+        # NaN at 2 substeps (zero-action probe, 300 steps); 4 substeps shows none.
+        num_substeps=4,
         debug_mode=False,
     )
     ovphysx = OvPhysxCfg()
@@ -304,28 +405,12 @@ class HandoverEnvCfg(DirectMARLEnvCfg):
         init_pos=(0.0, -1.0, 0.5),
         init_rot=(0.0, 0.0, 1.0, 0.0),
     )
-    actuated_joint_names = [
-        "robot0_WRJ1",
-        "robot0_WRJ0",
-        "robot0_FFJ3",
-        "robot0_FFJ2",
-        "robot0_FFJ1",
-        "robot0_MFJ3",
-        "robot0_MFJ2",
-        "robot0_MFJ1",
-        "robot0_RFJ3",
-        "robot0_RFJ2",
-        "robot0_RFJ1",
-        "robot0_LFJ4",
-        "robot0_LFJ3",
-        "robot0_LFJ2",
-        "robot0_LFJ1",
-        "robot0_THJ4",
-        "robot0_THJ3",
-        "robot0_THJ2",
-        "robot0_THJ1",
-        "robot0_THJ0",
-    ]
+    actuated_joint_names: PresetCfg = preset(
+        physx=_ACTUATED_JOINT_NAMES,
+        newton_mjwarp=_ACTUATED_JOINT_NAMES_NEWTON,
+        ovphysx=_ACTUATED_JOINT_NAMES,
+        default=_ACTUATED_JOINT_NAMES,
+    )
     fingertip_body_names = [
         "robot0_ffdistal",
         "robot0_mfdistal",

From 701b9c1f7f4f2a395667641b12cd128f4056388b Mon Sep 17 00:00:00 2001
From: jichuanh <jichuanh@nvidia.com>
Date: Thu, 9 Jul 2026 04:22:23 +0000
Subject: [PATCH 4/7] Apply the lumped-branch handover and constants updates

The handover cfg carries the Newton fixes from Part 4 plus the OVPhysX
presets; the Shadow cfg consumes the shared fingertip constants from
Part 3.
---
 .../core/handover/handover_env_cfg.py         | 95 ++++---------------
 .../config/shadow_hand/shadow_hand_env_cfg.py |  9 +-
 2 files changed, 23 insertions(+), 81 deletions(-)

diff --git a/source/isaaclab_tasks/isaaclab_tasks/core/handover/handover_env_cfg.py b/source/isaaclab_tasks/isaaclab_tasks/core/handover/handover_env_cfg.py
index 9b72c38ebc4b..8293b46c2895 100644
--- a/source/isaaclab_tasks/isaaclab_tasks/core/handover/handover_env_cfg.py
+++ b/source/isaaclab_tasks/isaaclab_tasks/core/handover/handover_env_cfg.py
@@ -20,6 +20,10 @@
 from isaaclab.sim.spawners.materials.physics_materials_cfg import RigidBodyMaterialCfg
 from isaaclab.utils.configclass import configclass
 
+from isaaclab_tasks.core.handover.handover_task_constants import (
+    ACTUATED_JOINT_NAMES_PRESET,
+    FINGERTIP_BODY_NAMES,
+)
 from isaaclab_tasks.core.reorient.config.shadow_hand.shadow_hand_env_cfg import ShadowHandRobotCfg
 from isaaclab_tasks.utils import PresetCfg, preset
 
@@ -132,57 +136,6 @@ class EventCfg:
 _SHADOW_HAND_NEWTON_CFG = ShadowHandRobotCfg().newton_mjwarp
 
 
-# Physical actuated set of the Shadow Hand (wrist + non-distal finger joints +
-# full thumb). The PhysX and OVPhysX asset names the finger chains J0..J3
-# (LF: J0..J4) with the tendon-coupled distal pair unactuated; the production
-# Newton asset renumbers the four finger chains by +1 (FF/MF/RF: J1..J4,
-# LF: J1..J5, distal = J1), so the same physical joints carry shifted names.
-_ACTUATED_JOINT_NAMES = [
-    "robot0_WRJ1",
-    "robot0_WRJ0",
-    "robot0_FFJ3",
-    "robot0_FFJ2",
-    "robot0_FFJ1",
-    "robot0_MFJ3",
-    "robot0_MFJ2",
-    "robot0_MFJ1",
-    "robot0_RFJ3",
-    "robot0_RFJ2",
-    "robot0_RFJ1",
-    "robot0_LFJ4",
-    "robot0_LFJ3",
-    "robot0_LFJ2",
-    "robot0_LFJ1",
-    "robot0_THJ4",
-    "robot0_THJ3",
-    "robot0_THJ2",
-    "robot0_THJ1",
-    "robot0_THJ0",
-]
-_ACTUATED_JOINT_NAMES_NEWTON = [
-    "robot0_WRJ1",
-    "robot0_WRJ0",
-    "robot0_FFJ4",
-    "robot0_FFJ3",
-    "robot0_FFJ2",
-    "robot0_MFJ4",
-    "robot0_MFJ3",
-    "robot0_MFJ2",
-    "robot0_RFJ4",
-    "robot0_RFJ3",
-    "robot0_RFJ2",
-    "robot0_LFJ5",
-    "robot0_LFJ4",
-    "robot0_LFJ3",
-    "robot0_LFJ2",
-    "robot0_THJ4",
-    "robot0_THJ3",
-    "robot0_THJ2",
-    "robot0_THJ1",
-    "robot0_THJ0",
-]
-
-
 def _quat_mul_xyzw(
     q1: tuple[float, float, float, float], q2: tuple[float, float, float, float]
 ) -> tuple[float, float, float, float]:
@@ -287,6 +240,19 @@ def _shadow_hand_cfg(
     return preset(default=physx_cfg, physx=physx_cfg, newton_mjwarp=newton_cfg, ovphysx=ovphysx_cfg)
 
 
+# Per-hand presets shared by the Direct environment and the manager scene.
+RIGHT_HAND_CFG = _shadow_hand_cfg(
+    prim_path="/World/envs/env_.*/RightRobot",
+    init_pos=(0.0, 0.0, 0.5),
+    init_rot=(0.0, 0.0, 0.0, 1.0),
+)
+LEFT_HAND_CFG = _shadow_hand_cfg(
+    prim_path="/World/envs/env_.*/LeftRobot",
+    init_pos=(0.0, -1.0, 0.5),
+    init_rot=(0.0, 0.0, 1.0, 0.0),
+)
+
+
 @configclass
 class ObjectCfg(PresetCfg):
     """Hand-over object preset.
@@ -395,29 +361,10 @@ class HandoverEnvCfg(DirectMARLEnvCfg):
         physics=PhysicsCfg(),
     )
     # robot
-    right_robot_cfg: PresetCfg = _shadow_hand_cfg(
-        prim_path="/World/envs/env_.*/RightRobot",
-        init_pos=(0.0, 0.0, 0.5),
-        init_rot=(0.0, 0.0, 0.0, 1.0),
-    )
-    left_robot_cfg: PresetCfg = _shadow_hand_cfg(
-        prim_path="/World/envs/env_.*/LeftRobot",
-        init_pos=(0.0, -1.0, 0.5),
-        init_rot=(0.0, 0.0, 1.0, 0.0),
-    )
-    actuated_joint_names: PresetCfg = preset(
-        physx=_ACTUATED_JOINT_NAMES,
-        newton_mjwarp=_ACTUATED_JOINT_NAMES_NEWTON,
-        ovphysx=_ACTUATED_JOINT_NAMES,
-        default=_ACTUATED_JOINT_NAMES,
-    )
-    fingertip_body_names = [
-        "robot0_ffdistal",
-        "robot0_mfdistal",
-        "robot0_rfdistal",
-        "robot0_lfdistal",
-        "robot0_thdistal",
-    ]
+    right_robot_cfg: PresetCfg = RIGHT_HAND_CFG
+    left_robot_cfg: PresetCfg = LEFT_HAND_CFG
+    actuated_joint_names: PresetCfg = ACTUATED_JOINT_NAMES_PRESET
+    fingertip_body_names = FINGERTIP_BODY_NAMES
 
     # in-hand object
     object_cfg: ObjectCfg = ObjectCfg()
diff --git a/source/isaaclab_tasks/isaaclab_tasks/core/reorient/config/shadow_hand/shadow_hand_env_cfg.py b/source/isaaclab_tasks/isaaclab_tasks/core/reorient/config/shadow_hand/shadow_hand_env_cfg.py
index 732f3805a3f5..2175945ac527 100644
--- a/source/isaaclab_tasks/isaaclab_tasks/core/reorient/config/shadow_hand/shadow_hand_env_cfg.py
+++ b/source/isaaclab_tasks/isaaclab_tasks/core/reorient/config/shadow_hand/shadow_hand_env_cfg.py
@@ -22,6 +22,7 @@
 from isaaclab.utils.configclass import configclass
 from isaaclab.utils.noise import GaussianNoiseCfg, NoiseModelWithAdditiveBiasCfg
 
+from isaaclab_tasks.core.reorient.reorient_task_constants import SHADOW_FINGERTIP_BODY_NAMES
 from isaaclab_tasks.utils import PresetCfg
 
 from isaaclab_assets.robots.shadow_hand import SHADOW_HAND_CFG
@@ -348,13 +349,7 @@ class ShadowHandEnvCfg(DirectRLEnvCfg):
         "robot0_THJ1",
         "robot0_THJ0",
     ]
-    fingertip_body_names = [
-        "robot0_ffdistal",
-        "robot0_mfdistal",
-        "robot0_rfdistal",
-        "robot0_lfdistal",
-        "robot0_thdistal",
-    ]
+    fingertip_body_names = SHADOW_FINGERTIP_BODY_NAMES
 
     # in-hand object
     object_cfg: ObjectCfg = ObjectCfg()

From 9c13b3e3aa3cffdefe8b1e77886f46b7977959e6 Mon Sep 17 00:00:00 2001
From: jichuanh <jichuanh@nvidia.com>
Date: Thu, 9 Jul 2026 08:22:29 +0000
Subject: [PATCH 5/7] Wire the Direct cfg scalars through the task constants

The Shadow and OpenAI Direct cfgs default their scalar fields from the
per-variant task constants and promote the shared scene and noise cfg
objects to module scope, so the manager counterparts consume one source
without instantiating a throwaway Direct cfg. The handover cfg carries
the same treatment plus the float64 hand-rotation composition.
---
 .../core/handover/handover_env_cfg.py         |  45 ++---
 .../config/shadow_hand/shadow_hand_env_cfg.py | 188 ++++++++++--------
 2 files changed, 130 insertions(+), 103 deletions(-)

diff --git a/source/isaaclab_tasks/isaaclab_tasks/core/handover/handover_env_cfg.py b/source/isaaclab_tasks/isaaclab_tasks/core/handover/handover_env_cfg.py
index 8293b46c2895..1beefcfa67fb 100644
--- a/source/isaaclab_tasks/isaaclab_tasks/core/handover/handover_env_cfg.py
+++ b/source/isaaclab_tasks/isaaclab_tasks/core/handover/handover_env_cfg.py
@@ -3,6 +3,7 @@
 #
 # SPDX-License-Identifier: BSD-3-Clause
 
+import warp as wp
 from isaaclab_newton.physics import MJWarpSolverCfg, NewtonCfg
 from isaaclab_ovphysx.physics import OvPhysxCfg
 from isaaclab_physx.physics import PhysxCfg
@@ -22,7 +23,15 @@
 
 from isaaclab_tasks.core.handover.handover_task_constants import (
     ACTUATED_JOINT_NAMES_PRESET,
+    DECIMATION,
+    DIST_REWARD_SCALE,
+    EPISODE_LENGTH_S,
+    FALL_DISTANCE,
     FINGERTIP_BODY_NAMES,
+    RESET_DOF_POS_NOISE,
+    RESET_DOF_VEL_NOISE,
+    RESET_POSITION_NOISE,
+    SUCCESS_DISTANCE_THRESHOLD,
 )
 from isaaclab_tasks.core.reorient.config.shadow_hand.shadow_hand_env_cfg import ShadowHandRobotCfg
 from isaaclab_tasks.utils import PresetCfg, preset
@@ -132,24 +141,10 @@ class EventCfg:
 # Reuse the single-agent Shadow Hand Newton port (USD path, ``rot`` reapplication
 # workaround, effort limits, joint regex). The multi-agent variant only diverges
 # in actuator gains (stiffness/damping bumped for the catch task) and adds a
-# ``distal_passive`` override for the J0 USD-baked values.
+# ``distal_passive`` override for the J1 USD-baked values.
 _SHADOW_HAND_NEWTON_CFG = ShadowHandRobotCfg().newton_mjwarp
 
 
-def _quat_mul_xyzw(
-    q1: tuple[float, float, float, float], q2: tuple[float, float, float, float]
-) -> tuple[float, float, float, float]:
-    """Compose two ``(x, y, z, w)`` quaternions (``q1`` applied on top of ``q2``)."""
-    x1, y1, z1, w1 = q1
-    x2, y2, z2, w2 = q2
-    return (
-        w1 * x2 + x1 * w2 + y1 * z2 - z1 * y2,
-        w1 * y2 - x1 * z2 + y1 * w2 + z1 * x2,
-        w1 * z2 + x1 * y2 - y1 * x2 + z1 * w2,
-        w1 * w2 - x1 * x2 - y1 * y2 - z1 * z2,
-    )
-
-
 def _shadow_hand_cfg(
     prim_path: str,
     init_pos: tuple[float, float, float],
@@ -189,7 +184,9 @@ def _shadow_hand_cfg(
     # task rotation must compose with that base rotation rather than replace
     # it — replacing left both palms heading 90 degrees off and the object
     # never rested in the right hand.
-    newton_rot = _quat_mul_xyzw(init_rot, _SHADOW_HAND_NEWTON_CFG.init_state.rot)
+    # Warp's quaternion type is (x, y, z, w); use the double variant so the
+    # composed cfg values keep float64 precision.
+    newton_rot = tuple(float(v) for v in wp.quatd(*init_rot) * wp.quatd(*_SHADOW_HAND_NEWTON_CFG.init_state.rot))
     newton_cfg = _SHADOW_HAND_NEWTON_CFG.replace(
         prim_path=prim_path,
         init_state=_SHADOW_HAND_NEWTON_CFG.init_state.replace(pos=init_pos, rot=newton_rot),
@@ -343,8 +340,8 @@ class PhysicsCfg(PresetCfg):
 @configclass
 class HandoverEnvCfg(DirectMARLEnvCfg):
     # env
-    decimation = 2
-    episode_length_s = 7.5
+    decimation = DECIMATION
+    episode_length_s = EPISODE_LENGTH_S
     possible_agents = ["right_hand", "left_hand"]
     action_spaces = {"right_hand": 20, "left_hand": 20}
     observation_spaces = {"right_hand": 157, "left_hand": 157}
@@ -382,15 +379,15 @@ class HandoverEnvCfg(DirectMARLEnvCfg):
     scene: InteractiveSceneCfg = InteractiveSceneCfg(num_envs=2048, env_spacing=1.5, replicate_physics=True)
 
     # reset
-    reset_position_noise = 0.01  # range of position at reset
-    reset_dof_pos_noise = 0.2  # range of dof pos at reset
-    reset_dof_vel_noise = 0.0  # range of dof vel at reset
+    reset_position_noise = RESET_POSITION_NOISE  # range of position at reset
+    reset_dof_pos_noise = RESET_DOF_POS_NOISE  # range of dof pos at reset
+    reset_dof_vel_noise = RESET_DOF_VEL_NOISE  # range of dof vel at reset
     # scales and constants
-    fall_dist = 0.24
+    fall_dist = FALL_DISTANCE
     vel_obs_scale = 0.2
     act_moving_average = 1.0
     # success criteria
-    success_distance_threshold: float = 0.1
+    success_distance_threshold: float = SUCCESS_DISTANCE_THRESHOLD
     """Object-to-goal distance below which the handover is considered successful [m]."""
     # reward-related scales
-    dist_reward_scale = 20.0
+    dist_reward_scale = DIST_REWARD_SCALE
diff --git a/source/isaaclab_tasks/isaaclab_tasks/core/reorient/config/shadow_hand/shadow_hand_env_cfg.py b/source/isaaclab_tasks/isaaclab_tasks/core/reorient/config/shadow_hand/shadow_hand_env_cfg.py
index 2175945ac527..5dfe6713922f 100644
--- a/source/isaaclab_tasks/isaaclab_tasks/core/reorient/config/shadow_hand/shadow_hand_env_cfg.py
+++ b/source/isaaclab_tasks/isaaclab_tasks/core/reorient/config/shadow_hand/shadow_hand_env_cfg.py
@@ -22,7 +22,47 @@
 from isaaclab.utils.configclass import configclass
 from isaaclab.utils.noise import GaussianNoiseCfg, NoiseModelWithAdditiveBiasCfg
 
-from isaaclab_tasks.core.reorient.reorient_task_constants import SHADOW_FINGERTIP_BODY_NAMES
+from isaaclab_tasks.core.reorient.reorient_task_constants import (
+    OPENAI_ACT_MOVING_AVERAGE,
+    OPENAI_ACTION_PENALTY_SCALE,
+    OPENAI_AV_FACTOR,
+    OPENAI_DECIMATION,
+    OPENAI_DIST_REWARD_SCALE,
+    OPENAI_EPISODE_LENGTH_S,
+    OPENAI_FALL_PENALTY,
+    OPENAI_FORCE_TORQUE_OBS_SCALE,
+    OPENAI_MAX_CONSECUTIVE_SUCCESS,
+    OPENAI_REACH_GOAL_BONUS,
+    OPENAI_RESET_DOF_POS_NOISE,
+    OPENAI_RESET_DOF_VEL_NOISE,
+    OPENAI_RESET_POSITION_NOISE,
+    OPENAI_ROT_EPS,
+    OPENAI_ROT_REWARD_SCALE,
+    OPENAI_SIM_DT,
+    OPENAI_SUCCESS_TOLERANCE,
+    OPENAI_VEL_OBS_SCALE,
+    SHADOW_ACT_MOVING_AVERAGE,
+    SHADOW_ACTION_PENALTY_SCALE,
+    SHADOW_ACTUATED_JOINT_NAMES,
+    SHADOW_AV_FACTOR,
+    SHADOW_DECIMATION,
+    SHADOW_DIST_REWARD_SCALE,
+    SHADOW_EPISODE_LENGTH_S,
+    SHADOW_FALL_DIST,
+    SHADOW_FALL_PENALTY,
+    SHADOW_FINGERTIP_BODY_NAMES,
+    SHADOW_FORCE_TORQUE_OBS_SCALE,
+    SHADOW_REACH_GOAL_BONUS,
+    SHADOW_RESET_DOF_POS_NOISE,
+    SHADOW_RESET_DOF_VEL_NOISE,
+    SHADOW_RESET_POSITION_NOISE,
+    SHADOW_ROT_EPS,
+    SHADOW_ROT_REWARD_SCALE,
+    SHADOW_SIM_DT,
+    SHADOW_SUCCESS_COUNT_THRESHOLD,
+    SHADOW_SUCCESS_TOLERANCE,
+    SHADOW_VEL_OBS_SCALE,
+)
 from isaaclab_tasks.utils import PresetCfg
 
 from isaaclab_assets.robots.shadow_hand import SHADOW_HAND_CFG
@@ -307,11 +347,25 @@ class PhysicsCfg(PresetCfg):
     newton_kamino = NewtonCfg(solver_cfg=KaminoSolverCfg(max_contacts_per_world=128))
 
 
+# Scene pieces shared verbatim by the manager-based variants.
+ROBOT_CFG = ShadowHandRobotCfg()
+OBJECT_CFG = ObjectCfg()
+GOAL_OBJECT_CFG = VisualizationMarkersCfg(
+    prim_path="/Visuals/goal_marker",
+    markers={
+        "goal": sim_utils.UsdFileCfg(
+            usd_path=f"{ISAAC_NUCLEUS_DIR}/Props/Blocks/DexCube/dex_cube_instanceable.usd",
+            scale=(1.0, 1.0, 1.0),
+        )
+    },
+)
+
+
 @configclass
 class ShadowHandEnvCfg(DirectRLEnvCfg):
     # env
-    decimation = 2
-    episode_length_s = 10.0
+    decimation = SHADOW_DECIMATION
+    episode_length_s = SHADOW_EPISODE_LENGTH_S
     action_space = 20
     observation_space = 157  # (full)
     state_space = 0
@@ -320,79 +374,61 @@ class ShadowHandEnvCfg(DirectRLEnvCfg):
 
     # simulation
     sim: SimulationCfg = SimulationCfg(
-        dt=1 / 120,
+        dt=SHADOW_SIM_DT,
         render_interval=decimation,
         physics_material=RigidBodyMaterialCfg(static_friction=1.0, dynamic_friction=1.0),
         physics=PhysicsCfg(),
     )
     # robot
-    robot_cfg: ShadowHandRobotCfg = ShadowHandRobotCfg()
-    actuated_joint_names = [
-        "robot0_WRJ1",
-        "robot0_WRJ0",
-        "robot0_FFJ3",
-        "robot0_FFJ2",
-        "robot0_FFJ1",
-        "robot0_MFJ3",
-        "robot0_MFJ2",
-        "robot0_MFJ1",
-        "robot0_RFJ3",
-        "robot0_RFJ2",
-        "robot0_RFJ1",
-        "robot0_LFJ4",
-        "robot0_LFJ3",
-        "robot0_LFJ2",
-        "robot0_LFJ1",
-        "robot0_THJ4",
-        "robot0_THJ3",
-        "robot0_THJ2",
-        "robot0_THJ1",
-        "robot0_THJ0",
-    ]
+    robot_cfg: ShadowHandRobotCfg = ROBOT_CFG
+    actuated_joint_names = SHADOW_ACTUATED_JOINT_NAMES
     fingertip_body_names = SHADOW_FINGERTIP_BODY_NAMES
 
     # in-hand object
-    object_cfg: ObjectCfg = ObjectCfg()
+    object_cfg: ObjectCfg = OBJECT_CFG
     # goal object
-    goal_object_cfg: VisualizationMarkersCfg = VisualizationMarkersCfg(
-        prim_path="/Visuals/goal_marker",
-        markers={
-            "goal": sim_utils.UsdFileCfg(
-                usd_path=f"{ISAAC_NUCLEUS_DIR}/Props/Blocks/DexCube/dex_cube_instanceable.usd",
-                scale=(1.0, 1.0, 1.0),
-            )
-        },
-    )
+    goal_object_cfg: VisualizationMarkersCfg = GOAL_OBJECT_CFG
     # scene — use ShadowHandSceneCfg so that presets=newton_mjwarp disables clone_in_fabric automatically
     scene: ShadowHandSceneCfg = ShadowHandSceneCfg()
 
     # reset
-    reset_position_noise = 0.01  # range of position at reset
-    reset_dof_pos_noise = 0.2  # range of dof pos at reset
-    reset_dof_vel_noise = 0.0  # range of dof vel at reset
+    reset_position_noise = SHADOW_RESET_POSITION_NOISE  # range of position at reset
+    reset_dof_pos_noise = SHADOW_RESET_DOF_POS_NOISE  # range of dof pos at reset
+    reset_dof_vel_noise = SHADOW_RESET_DOF_VEL_NOISE  # range of dof vel at reset
     # reward scales
-    dist_reward_scale = -10.0
-    rot_reward_scale = 1.0
-    rot_eps = 0.1
-    action_penalty_scale = -0.0002
-    reach_goal_bonus = 250
-    fall_penalty = 0
-    fall_dist = 0.24
-    vel_obs_scale = 0.2
-    success_tolerance = 0.1
+    dist_reward_scale = SHADOW_DIST_REWARD_SCALE
+    rot_reward_scale = SHADOW_ROT_REWARD_SCALE
+    rot_eps = SHADOW_ROT_EPS
+    action_penalty_scale = SHADOW_ACTION_PENALTY_SCALE
+    reach_goal_bonus = SHADOW_REACH_GOAL_BONUS
+    fall_penalty = SHADOW_FALL_PENALTY
+    fall_dist = SHADOW_FALL_DIST
+    vel_obs_scale = SHADOW_VEL_OBS_SCALE
+    success_tolerance = SHADOW_SUCCESS_TOLERANCE
     max_consecutive_success = 0
-    success_count_threshold: int = 1
+    success_count_threshold: int = SHADOW_SUCCESS_COUNT_THRESHOLD
     """Minimum number of goals reached in an episode to count it as a successful episode."""
-    av_factor = 0.1
-    act_moving_average = 1.0
-    force_torque_obs_scale = 10.0
+    av_factor = SHADOW_AV_FACTOR
+    act_moving_average = SHADOW_ACT_MOVING_AVERAGE
+    force_torque_obs_scale = SHADOW_FORCE_TORQUE_OBS_SCALE
+
+
+# Per-step gaussian noise + reset-sampled bias, shared verbatim by the manager-based variant.
+OPENAI_ACTION_NOISE_CFG = NoiseModelWithAdditiveBiasCfg(
+    noise_cfg=GaussianNoiseCfg(mean=0.0, std=0.05, operation="add"),
+    bias_noise_cfg=GaussianNoiseCfg(mean=0.0, std=0.015, operation="abs"),
+)
+OPENAI_OBSERVATION_NOISE_CFG = NoiseModelWithAdditiveBiasCfg(
+    noise_cfg=GaussianNoiseCfg(mean=0.0, std=0.002, operation="add"),
+    bias_noise_cfg=GaussianNoiseCfg(mean=0.0, std=0.0001, operation="abs"),
+)
 
 
 @configclass
 class ShadowHandOpenAIEnvCfg(ShadowHandEnvCfg):
     # env
-    decimation = 3
-    episode_length_s = 8.0
+    decimation = OPENAI_DECIMATION
+    episode_length_s = OPENAI_EPISODE_LENGTH_S
     action_space = 20
     observation_space = 42
     state_space = 187
@@ -400,37 +436,31 @@ class ShadowHandOpenAIEnvCfg(ShadowHandEnvCfg):
     obs_type = "openai"
     # simulation
     sim: SimulationCfg = SimulationCfg(
-        dt=1 / 60,
+        dt=OPENAI_SIM_DT,
         render_interval=decimation,
         physics_material=RigidBodyMaterialCfg(static_friction=1.0, dynamic_friction=1.0),
         physics=PhysicsCfg(),
     )
     # reset
-    reset_position_noise = 0.01  # range of position at reset
-    reset_dof_pos_noise = 0.2  # range of dof pos at reset
-    reset_dof_vel_noise = 0.0  # range of dof vel at reset
+    reset_position_noise = OPENAI_RESET_POSITION_NOISE  # range of position at reset
+    reset_dof_pos_noise = OPENAI_RESET_DOF_POS_NOISE  # range of dof pos at reset
+    reset_dof_vel_noise = OPENAI_RESET_DOF_VEL_NOISE  # range of dof vel at reset
     # reward scales
-    dist_reward_scale = -10.0
-    rot_reward_scale = 1.0
-    rot_eps = 0.1
-    action_penalty_scale = -0.0002
-    reach_goal_bonus = 250
-    fall_penalty = -50
-    vel_obs_scale = 0.2
-    success_tolerance = 0.4
-    max_consecutive_success = 50
-    av_factor = 0.1
-    act_moving_average = 0.3
-    force_torque_obs_scale = 10.0
+    dist_reward_scale = OPENAI_DIST_REWARD_SCALE
+    rot_reward_scale = OPENAI_ROT_REWARD_SCALE
+    rot_eps = OPENAI_ROT_EPS
+    action_penalty_scale = OPENAI_ACTION_PENALTY_SCALE
+    reach_goal_bonus = OPENAI_REACH_GOAL_BONUS
+    fall_penalty = OPENAI_FALL_PENALTY
+    vel_obs_scale = OPENAI_VEL_OBS_SCALE
+    success_tolerance = OPENAI_SUCCESS_TOLERANCE
+    max_consecutive_success = OPENAI_MAX_CONSECUTIVE_SUCCESS
+    av_factor = OPENAI_AV_FACTOR
+    act_moving_average = OPENAI_ACT_MOVING_AVERAGE
+    force_torque_obs_scale = OPENAI_FORCE_TORQUE_OBS_SCALE
     # domain randomization config
     events: ShadowHandEventCfg = ShadowHandEventCfg()
     # at every time-step add gaussian noise + bias. The bias is a gaussian sampled at reset
-    action_noise_model: NoiseModelWithAdditiveBiasCfg = NoiseModelWithAdditiveBiasCfg(
-        noise_cfg=GaussianNoiseCfg(mean=0.0, std=0.05, operation="add"),
-        bias_noise_cfg=GaussianNoiseCfg(mean=0.0, std=0.015, operation="abs"),
-    )
+    action_noise_model: NoiseModelWithAdditiveBiasCfg = OPENAI_ACTION_NOISE_CFG
     # at every time-step add gaussian noise + bias. The bias is a gaussian sampled at reset
-    observation_noise_model: NoiseModelWithAdditiveBiasCfg = NoiseModelWithAdditiveBiasCfg(
-        noise_cfg=GaussianNoiseCfg(mean=0.0, std=0.002, operation="add"),
-        bias_noise_cfg=GaussianNoiseCfg(mean=0.0, std=0.0001, operation="abs"),
-    )
+    observation_noise_model: NoiseModelWithAdditiveBiasCfg = OPENAI_OBSERVATION_NOISE_CFG

From 398c541aab4d47ce5d6a6cda8dea1212d99f1123 Mon Sep 17 00:00:00 2001
From: jichuanh <jichuanh@nvidia.com>
Date: Sat, 11 Jul 2026 00:28:02 +0000
Subject: [PATCH 6/7] Sync the handover cfg constants and trim cfg tests

The handover env cfg reads SIM_DT and VEL_OBS_SCALE from the shared
constants module instead of literals. The cfg-content test files
(Shadow cfg, OVPhysX preset acceptance) are dropped per the
tests-assert-behavior principle; the consolidated kernel behavior
suite ships with Part 11.
---
 .../core/handover/handover_env_cfg.py         |  6 +-
 .../core/test_dexterous_ovphysx_presets.py    | 47 -----------
 .../test/core/test_shadow_hand_env_cfg.py     | 80 -------------------
 3 files changed, 4 insertions(+), 129 deletions(-)
 delete mode 100644 source/isaaclab_tasks/test/core/test_dexterous_ovphysx_presets.py
 delete mode 100644 source/isaaclab_tasks/test/core/test_shadow_hand_env_cfg.py

diff --git a/source/isaaclab_tasks/isaaclab_tasks/core/handover/handover_env_cfg.py b/source/isaaclab_tasks/isaaclab_tasks/core/handover/handover_env_cfg.py
index 1beefcfa67fb..189c7dd6995d 100644
--- a/source/isaaclab_tasks/isaaclab_tasks/core/handover/handover_env_cfg.py
+++ b/source/isaaclab_tasks/isaaclab_tasks/core/handover/handover_env_cfg.py
@@ -31,7 +31,9 @@
     RESET_DOF_POS_NOISE,
     RESET_DOF_VEL_NOISE,
     RESET_POSITION_NOISE,
+    SIM_DT,
     SUCCESS_DISTANCE_THRESHOLD,
+    VEL_OBS_SCALE,
 )
 from isaaclab_tasks.core.reorient.config.shadow_hand.shadow_hand_env_cfg import ShadowHandRobotCfg
 from isaaclab_tasks.utils import PresetCfg, preset
@@ -349,7 +351,7 @@ class HandoverEnvCfg(DirectMARLEnvCfg):
 
     # simulation
     sim: SimulationCfg = SimulationCfg(
-        dt=1 / 120,
+        dt=SIM_DT,
         render_interval=decimation,
         physics_material=RigidBodyMaterialCfg(
             static_friction=1.0,
@@ -384,7 +386,7 @@ class HandoverEnvCfg(DirectMARLEnvCfg):
     reset_dof_vel_noise = RESET_DOF_VEL_NOISE  # range of dof vel at reset
     # scales and constants
     fall_dist = FALL_DISTANCE
-    vel_obs_scale = 0.2
+    vel_obs_scale = VEL_OBS_SCALE
     act_moving_average = 1.0
     # success criteria
     success_distance_threshold: float = SUCCESS_DISTANCE_THRESHOLD
diff --git a/source/isaaclab_tasks/test/core/test_dexterous_ovphysx_presets.py b/source/isaaclab_tasks/test/core/test_dexterous_ovphysx_presets.py
deleted file mode 100644
index 0c4bb125093e..000000000000
--- a/source/isaaclab_tasks/test/core/test_dexterous_ovphysx_presets.py
+++ /dev/null
@@ -1,47 +0,0 @@
-# Copyright (c) 2022-2026, The Isaac Lab Project Developers (https://github.com/isaac-sim/IsaacLab/blob/main/CONTRIBUTORS.md).
-# All rights reserved.
-#
-# SPDX-License-Identifier: BSD-3-Clause
-
-"""Configuration tests for OVPhysX support in assigned dexterous tasks."""
-
-import pytest
-from isaaclab_newton.physics import NewtonCfg
-from isaaclab_ovphysx.physics import OvPhysxCfg
-
-from isaaclab_tasks.core.handover.handover_env_cfg import HandoverEnvCfg
-from isaaclab_tasks.core.reorient.config.allegro_hand.allegro_hand_direct_env_cfg import AllegroHandEnvCfg
-from isaaclab_tasks.core.reorient.config.shadow_hand.shadow_hand_env_cfg import (
-    ShadowHandEnvCfg,
-    ShadowHandOpenAIEnvCfg,
-)
-from isaaclab_tasks.utils.hydra import collect_presets, resolve_presets
-
-
-@pytest.mark.parametrize(
-    "env_cfg_type",
-    [
-        pytest.param(AllegroHandEnvCfg, id="allegro_direct"),
-        pytest.param(ShadowHandEnvCfg, id="shadow_direct"),
-        pytest.param(ShadowHandOpenAIEnvCfg, id="shadow_openai_ff"),
-        pytest.param(HandoverEnvCfg, id="handover"),
-    ],
-)
-def test_ovphysx_physics_preset_resolves_for_assigned_dexterous_variants(env_cfg_type):
-    """Verify every assigned variant resolves its physics preset to OVPhysX."""
-    env_cfg = env_cfg_type()
-
-    assert "ovphysx" in collect_presets(env_cfg)["sim.physics"]
-
-    resolved_cfg = resolve_presets(env_cfg, {"ovphysx"})
-
-    assert isinstance(resolved_cfg.sim.physics, OvPhysxCfg)
-
-
-@pytest.mark.parametrize("env_cfg_type", [HandoverEnvCfg])
-def test_newton_physics_and_scene_presets_resolve_for_handover(env_cfg_type):
-    """Verify Direct Handover resolves Newton physics and cloning together."""
-    resolved_cfg = resolve_presets(env_cfg_type(), {"newton_mjwarp"})
-
-    assert isinstance(resolved_cfg.sim.physics, NewtonCfg)
-    assert not resolved_cfg.scene.clone_in_fabric
diff --git a/source/isaaclab_tasks/test/core/test_shadow_hand_env_cfg.py b/source/isaaclab_tasks/test/core/test_shadow_hand_env_cfg.py
deleted file mode 100644
index beb68d7a81f3..000000000000
--- a/source/isaaclab_tasks/test/core/test_shadow_hand_env_cfg.py
+++ /dev/null
@@ -1,80 +0,0 @@
-# Copyright (c) 2022-2026, The Isaac Lab Project Developers (https://github.com/isaac-sim/IsaacLab/blob/main/CONTRIBUTORS.md).
-# All rights reserved.
-#
-# SPDX-License-Identifier: BSD-3-Clause
-
-"""Tests for the shared Shadow Hand environment configuration."""
-
-import pytest
-
-from isaaclab.utils.assets import ISAAC_NUCLEUS_DIR
-
-from isaaclab_tasks.core.reorient.config.shadow_hand.shadow_hand_env_cfg import (
-    NewtonEventCfg,
-    PhysxEventCfg,
-    ShadowHandEnvCfg,
-)
-
-from isaaclab_assets import SHADOW_HAND_CFG
-
-
-def test_events_randomize_fixed_tendons_on_both_backends():
-    """Verify PhysX and Newton events preserve fixed-tendon randomization."""
-    for event_cfg in (PhysxEventCfg(), NewtonEventCfg()):
-        event = event_cfg.robot_tendon_properties
-
-        assert event.func.__name__ == "randomize_fixed_tendon_parameters"
-        assert event.params["asset_cfg"].fixed_tendon_names == ".*"
-
-
-def test_shadow_variants_use_supported_asset_and_backend_physics_layers():
-    """Verify each backend preset uses the production Shadow Hand asset it supports."""
-    cfg = ShadowHandEnvCfg()
-    legacy_path = f"{ISAAC_NUCLEUS_DIR}/Robots/ShadowRobot/ShadowHand/shadow_hand_instanceable.usd"
-
-    assert SHADOW_HAND_CFG.spawn.usd_path == legacy_path
-    assert SHADOW_HAND_CFG.spawn.fixed_tendons_props is not None
-    assert cfg.robot_cfg.physx.spawn.usd_path == legacy_path
-    assert cfg.robot_cfg.ovphysx.spawn.usd_path == legacy_path
-    assert cfg.robot_cfg.newton_mjwarp.spawn.usd_path == (
-        f"{ISAAC_NUCLEUS_DIR}/Robots/ShadowRobot/ShadowHandNewton/shadow_hand_instanceable.usda"
-    )
-    assert cfg.robot_cfg.physx.spawn.variants is None
-    assert cfg.robot_cfg.ovphysx.spawn.variants is None
-    assert cfg.robot_cfg.newton_mjwarp.spawn.variants is None
-    assert cfg.robot_cfg.ovphysx.spawn.fixed_tendons_props is None
-    assert cfg.robot_cfg.physx.init_state.rot == (0.0, 0.0, 0.0, 1.0)
-    assert cfg.robot_cfg.ovphysx.init_state.rot == (0.0, 0.0, 0.0, 1.0)
-    assert cfg.robot_cfg.newton_mjwarp.spawn.fixed_tendons_props.damping == 0.1
-    assert cfg.robot_cfg.newton_mjwarp.init_state.rot == (0.0, 0.0, -0.70710678118, 0.70710678118)
-    assert sum(value**2 for value in cfg.robot_cfg.newton_mjwarp.init_state.rot) == pytest.approx(1.0)
-    assert cfg.sim.physics.newton_mjwarp.num_substeps == 2
-
-
-def test_shadow_joint_mapping_preserves_twenty_action_contract():
-    """Verify the actuated-joint list preserves the legacy 20-action order."""
-    cfg = ShadowHandEnvCfg()
-
-    assert cfg.action_space == len(cfg.actuated_joint_names) == 20
-    assert cfg.actuated_joint_names == [
-        "robot0_WRJ1",
-        "robot0_WRJ0",
-        "robot0_FFJ3",
-        "robot0_FFJ2",
-        "robot0_FFJ1",
-        "robot0_MFJ3",
-        "robot0_MFJ2",
-        "robot0_MFJ1",
-        "robot0_RFJ3",
-        "robot0_RFJ2",
-        "robot0_RFJ1",
-        "robot0_LFJ4",
-        "robot0_LFJ3",
-        "robot0_LFJ2",
-        "robot0_LFJ1",
-        "robot0_THJ4",
-        "robot0_THJ3",
-        "robot0_THJ2",
-        "robot0_THJ1",
-        "robot0_THJ0",
-    ]

From 8fb580c4aefc502d56b30bf067c6dc9461ef2bac Mon Sep 17 00:00:00 2001
From: Jichuan Hu <jichuanh@nvidia.com>
Date: Tue, 14 Jul 2026 02:07:23 -0700
Subject: [PATCH 7/7] Sync the Direct configurations to per-paradigm parameters

The Shadow and handover Direct configurations define their scalar
task parameters as flat literal fields (read live by the Direct
environments), replacing the shared-constants indirection, and pick
up the renamed *_task_base structural modules.
---
 .../core/handover/handover_env_cfg.py         |  70 ++++----
 .../config/shadow_hand/shadow_hand_env_cfg.py | 151 ++++++++----------
 2 files changed, 92 insertions(+), 129 deletions(-)

diff --git a/source/isaaclab_tasks/isaaclab_tasks/core/handover/handover_env_cfg.py b/source/isaaclab_tasks/isaaclab_tasks/core/handover/handover_env_cfg.py
index 189c7dd6995d..64b4a10758c0 100644
--- a/source/isaaclab_tasks/isaaclab_tasks/core/handover/handover_env_cfg.py
+++ b/source/isaaclab_tasks/isaaclab_tasks/core/handover/handover_env_cfg.py
@@ -18,22 +18,14 @@
 from isaaclab.markers import VisualizationMarkersCfg
 from isaaclab.scene import InteractiveSceneCfg
 from isaaclab.sim import SimulationCfg
-from isaaclab.sim.spawners.materials.physics_materials_cfg import RigidBodyMaterialCfg
+from isaaclab.sim.spawners.materials import RigidBodyMaterialBaseCfg
 from isaaclab.utils.configclass import configclass
 
-from isaaclab_tasks.core.handover.handover_task_constants import (
+from isaaclab_tasks.core.handover.handover_task_base import (
     ACTUATED_JOINT_NAMES_PRESET,
-    DECIMATION,
-    DIST_REWARD_SCALE,
-    EPISODE_LENGTH_S,
-    FALL_DISTANCE,
     FINGERTIP_BODY_NAMES,
-    RESET_DOF_POS_NOISE,
-    RESET_DOF_VEL_NOISE,
-    RESET_POSITION_NOISE,
-    SIM_DT,
-    SUCCESS_DISTANCE_THRESHOLD,
-    VEL_OBS_SCALE,
+    GOAL_MARKER_CFG,
+    OBJECT_RADIUS,
 )
 from isaaclab_tasks.core.reorient.config.shadow_hand.shadow_hand_env_cfg import ShadowHandRobotCfg
 from isaaclab_tasks.utils import PresetCfg, preset
@@ -267,7 +259,7 @@ class ObjectCfg(PresetCfg):
     physx = RigidObjectCfg(
         prim_path="/World/envs/env_.*/object",
         spawn=sim_utils.SphereCfg(
-            radius=0.0335,
+            radius=OBJECT_RADIUS,
             visual_material=sim_utils.PreviewSurfaceCfg(diffuse_color=(0.8, 1.0, 0.0)),
             physics_material=sim_utils.RigidBodyMaterialCfg(static_friction=0.7),
             rigid_props=sim_utils.RigidBodyPropertiesCfg(
@@ -288,7 +280,7 @@ class ObjectCfg(PresetCfg):
     newton_mjwarp = RigidObjectCfg(
         prim_path="/World/envs/env_.*/object",
         spawn=sim_utils.SphereCfg(
-            radius=0.0335,
+            radius=OBJECT_RADIUS,
             visual_material=sim_utils.PreviewSurfaceCfg(diffuse_color=(0.8, 1.0, 0.0)),
             rigid_props=sim_utils.RigidBodyPropertiesCfg(
                 kinematic_enabled=False,
@@ -339,26 +331,30 @@ class PhysicsCfg(PresetCfg):
     default = physx
 
 
+# Simulation settings shared by the Direct and manager variants (configclass
+# deep-copies these defaults per cfg instance). The solver-common base material
+# is sufficient: only friction values are set, so no PhysX-specific
+# ``physxMaterial`` attributes are authored.
+HANDOVER_SIM_CFG = SimulationCfg(
+    dt=1 / 120,
+    render_interval=2,
+    physics_material=RigidBodyMaterialBaseCfg(static_friction=1.0, dynamic_friction=1.0),
+    physics=PhysicsCfg(),
+)
+
+
 @configclass
 class HandoverEnvCfg(DirectMARLEnvCfg):
     # env
-    decimation = DECIMATION
-    episode_length_s = EPISODE_LENGTH_S
+    decimation = 2
+    episode_length_s = 7.5
     possible_agents = ["right_hand", "left_hand"]
     action_spaces = {"right_hand": 20, "left_hand": 20}
     observation_spaces = {"right_hand": 157, "left_hand": 157}
     state_space = 290
 
     # simulation
-    sim: SimulationCfg = SimulationCfg(
-        dt=SIM_DT,
-        render_interval=decimation,
-        physics_material=RigidBodyMaterialCfg(
-            static_friction=1.0,
-            dynamic_friction=1.0,
-        ),
-        physics=PhysicsCfg(),
-    )
+    sim: SimulationCfg = HANDOVER_SIM_CFG
     # robot
     right_robot_cfg: PresetCfg = RIGHT_HAND_CFG
     left_robot_cfg: PresetCfg = LEFT_HAND_CFG
@@ -368,28 +364,20 @@ class HandoverEnvCfg(DirectMARLEnvCfg):
     # in-hand object
     object_cfg: ObjectCfg = ObjectCfg()
     # goal object
-    goal_object_cfg: VisualizationMarkersCfg = VisualizationMarkersCfg(
-        prim_path="/Visuals/goal_marker",
-        markers={
-            "goal": sim_utils.SphereCfg(
-                radius=0.0335,
-                visual_material=sim_utils.PreviewSurfaceCfg(diffuse_color=(0.4, 0.3, 1.0)),
-            ),
-        },
-    )
+    goal_object_cfg: VisualizationMarkersCfg = GOAL_MARKER_CFG
     # scene
     scene: InteractiveSceneCfg = InteractiveSceneCfg(num_envs=2048, env_spacing=1.5, replicate_physics=True)
 
     # reset
-    reset_position_noise = RESET_POSITION_NOISE  # range of position at reset
-    reset_dof_pos_noise = RESET_DOF_POS_NOISE  # range of dof pos at reset
-    reset_dof_vel_noise = RESET_DOF_VEL_NOISE  # range of dof vel at reset
+    reset_position_noise = 0.01  # range of position at reset
+    reset_dof_pos_noise = 0.2  # range of dof pos at reset
+    reset_dof_vel_noise = 0.0  # range of dof vel at reset
     # scales and constants
-    fall_dist = FALL_DISTANCE
-    vel_obs_scale = VEL_OBS_SCALE
+    fall_dist = 0.24
+    vel_obs_scale = 0.2
     act_moving_average = 1.0
     # success criteria
-    success_distance_threshold: float = SUCCESS_DISTANCE_THRESHOLD
+    success_distance_threshold: float = 0.1
     """Object-to-goal distance below which the handover is considered successful [m]."""
     # reward-related scales
-    dist_reward_scale = DIST_REWARD_SCALE
+    dist_reward_scale = 20.0
diff --git a/source/isaaclab_tasks/isaaclab_tasks/core/reorient/config/shadow_hand/shadow_hand_env_cfg.py b/source/isaaclab_tasks/isaaclab_tasks/core/reorient/config/shadow_hand/shadow_hand_env_cfg.py
index 5dfe6713922f..c605f78cc6dd 100644
--- a/source/isaaclab_tasks/isaaclab_tasks/core/reorient/config/shadow_hand/shadow_hand_env_cfg.py
+++ b/source/isaaclab_tasks/isaaclab_tasks/core/reorient/config/shadow_hand/shadow_hand_env_cfg.py
@@ -17,51 +17,14 @@
 from isaaclab.markers import VisualizationMarkersCfg
 from isaaclab.scene import InteractiveSceneCfg
 from isaaclab.sim import SimulationCfg
-from isaaclab.sim.spawners.materials.physics_materials_cfg import RigidBodyMaterialCfg
+from isaaclab.sim.spawners.materials import RigidBodyMaterialBaseCfg
 from isaaclab.utils.assets import ISAAC_NUCLEUS_DIR
 from isaaclab.utils.configclass import configclass
 from isaaclab.utils.noise import GaussianNoiseCfg, NoiseModelWithAdditiveBiasCfg
 
-from isaaclab_tasks.core.reorient.reorient_task_constants import (
-    OPENAI_ACT_MOVING_AVERAGE,
-    OPENAI_ACTION_PENALTY_SCALE,
-    OPENAI_AV_FACTOR,
-    OPENAI_DECIMATION,
-    OPENAI_DIST_REWARD_SCALE,
-    OPENAI_EPISODE_LENGTH_S,
-    OPENAI_FALL_PENALTY,
-    OPENAI_FORCE_TORQUE_OBS_SCALE,
-    OPENAI_MAX_CONSECUTIVE_SUCCESS,
-    OPENAI_REACH_GOAL_BONUS,
-    OPENAI_RESET_DOF_POS_NOISE,
-    OPENAI_RESET_DOF_VEL_NOISE,
-    OPENAI_RESET_POSITION_NOISE,
-    OPENAI_ROT_EPS,
-    OPENAI_ROT_REWARD_SCALE,
-    OPENAI_SIM_DT,
-    OPENAI_SUCCESS_TOLERANCE,
-    OPENAI_VEL_OBS_SCALE,
-    SHADOW_ACT_MOVING_AVERAGE,
-    SHADOW_ACTION_PENALTY_SCALE,
+from isaaclab_tasks.core.reorient.reorient_task_base import (
     SHADOW_ACTUATED_JOINT_NAMES,
-    SHADOW_AV_FACTOR,
-    SHADOW_DECIMATION,
-    SHADOW_DIST_REWARD_SCALE,
-    SHADOW_EPISODE_LENGTH_S,
-    SHADOW_FALL_DIST,
-    SHADOW_FALL_PENALTY,
     SHADOW_FINGERTIP_BODY_NAMES,
-    SHADOW_FORCE_TORQUE_OBS_SCALE,
-    SHADOW_REACH_GOAL_BONUS,
-    SHADOW_RESET_DOF_POS_NOISE,
-    SHADOW_RESET_DOF_VEL_NOISE,
-    SHADOW_RESET_POSITION_NOISE,
-    SHADOW_ROT_EPS,
-    SHADOW_ROT_REWARD_SCALE,
-    SHADOW_SIM_DT,
-    SHADOW_SUCCESS_COUNT_THRESHOLD,
-    SHADOW_SUCCESS_TOLERANCE,
-    SHADOW_VEL_OBS_SCALE,
 )
 from isaaclab_tasks.utils import PresetCfg
 
@@ -312,10 +275,16 @@ class ShadowHandSceneCfg(PresetCfg):
     """
 
     physx: InteractiveSceneCfg = InteractiveSceneCfg(
-        num_envs=8192, env_spacing=0.75, replicate_physics=True, clone_in_fabric=True
+        num_envs=8192,
+        env_spacing=0.75,
+        replicate_physics=True,
+        clone_in_fabric=True,
     )
     newton_mjwarp: InteractiveSceneCfg = InteractiveSceneCfg(
-        num_envs=8192, env_spacing=0.75, replicate_physics=True, clone_in_fabric=False
+        num_envs=8192,
+        env_spacing=0.75,
+        replicate_physics=True,
+        clone_in_fabric=False,
     )
     default: InteractiveSceneCfg = physx
     newton_kamino = newton_mjwarp
@@ -359,13 +328,29 @@ class PhysicsCfg(PresetCfg):
         )
     },
 )
+# Simulation settings shared by the Direct and manager variants (configclass
+# deep-copies these defaults per cfg instance). The solver-common base material
+# is sufficient: only friction values are set, so no PhysX-specific
+# ``physxMaterial`` attributes are authored.
+SHADOW_SIM_CFG = SimulationCfg(
+    dt=1 / 120,
+    render_interval=2,
+    physics_material=RigidBodyMaterialBaseCfg(static_friction=1.0, dynamic_friction=1.0),
+    physics=PhysicsCfg(),
+)
+OPENAI_SIM_CFG = SimulationCfg(
+    dt=1 / 60,
+    render_interval=3,
+    physics_material=RigidBodyMaterialBaseCfg(static_friction=1.0, dynamic_friction=1.0),
+    physics=PhysicsCfg(),
+)
 
 
 @configclass
 class ShadowHandEnvCfg(DirectRLEnvCfg):
     # env
-    decimation = SHADOW_DECIMATION
-    episode_length_s = SHADOW_EPISODE_LENGTH_S
+    decimation = 2
+    episode_length_s = 10.0
     action_space = 20
     observation_space = 157  # (full)
     state_space = 0
@@ -373,12 +358,7 @@ class ShadowHandEnvCfg(DirectRLEnvCfg):
     obs_type = "full"
 
     # simulation
-    sim: SimulationCfg = SimulationCfg(
-        dt=SHADOW_SIM_DT,
-        render_interval=decimation,
-        physics_material=RigidBodyMaterialCfg(static_friction=1.0, dynamic_friction=1.0),
-        physics=PhysicsCfg(),
-    )
+    sim: SimulationCfg = SHADOW_SIM_CFG
     # robot
     robot_cfg: ShadowHandRobotCfg = ROBOT_CFG
     actuated_joint_names = SHADOW_ACTUATED_JOINT_NAMES
@@ -392,25 +372,25 @@ class ShadowHandEnvCfg(DirectRLEnvCfg):
     scene: ShadowHandSceneCfg = ShadowHandSceneCfg()
 
     # reset
-    reset_position_noise = SHADOW_RESET_POSITION_NOISE  # range of position at reset
-    reset_dof_pos_noise = SHADOW_RESET_DOF_POS_NOISE  # range of dof pos at reset
-    reset_dof_vel_noise = SHADOW_RESET_DOF_VEL_NOISE  # range of dof vel at reset
+    reset_position_noise = 0.01  # range of position at reset
+    reset_dof_pos_noise = 0.2  # range of dof pos at reset
+    reset_dof_vel_noise = 0.0  # range of dof vel at reset
     # reward scales
-    dist_reward_scale = SHADOW_DIST_REWARD_SCALE
-    rot_reward_scale = SHADOW_ROT_REWARD_SCALE
-    rot_eps = SHADOW_ROT_EPS
-    action_penalty_scale = SHADOW_ACTION_PENALTY_SCALE
-    reach_goal_bonus = SHADOW_REACH_GOAL_BONUS
-    fall_penalty = SHADOW_FALL_PENALTY
-    fall_dist = SHADOW_FALL_DIST
-    vel_obs_scale = SHADOW_VEL_OBS_SCALE
-    success_tolerance = SHADOW_SUCCESS_TOLERANCE
+    dist_reward_scale = -10.0
+    rot_reward_scale = 1.0
+    rot_eps = 0.1
+    action_penalty_scale = -0.0002
+    reach_goal_bonus = 250.0
+    fall_penalty = 0.0
+    fall_dist = 0.24
+    vel_obs_scale = 0.2
+    success_tolerance = 0.1
     max_consecutive_success = 0
-    success_count_threshold: int = SHADOW_SUCCESS_COUNT_THRESHOLD
+    success_count_threshold: int = 1
     """Minimum number of goals reached in an episode to count it as a successful episode."""
-    av_factor = SHADOW_AV_FACTOR
-    act_moving_average = SHADOW_ACT_MOVING_AVERAGE
-    force_torque_obs_scale = SHADOW_FORCE_TORQUE_OBS_SCALE
+    av_factor = 0.1
+    act_moving_average = 1.0
+    force_torque_obs_scale = 10.0
 
 
 # Per-step gaussian noise + reset-sampled bias, shared verbatim by the manager-based variant.
@@ -427,37 +407,32 @@ class ShadowHandEnvCfg(DirectRLEnvCfg):
 @configclass
 class ShadowHandOpenAIEnvCfg(ShadowHandEnvCfg):
     # env
-    decimation = OPENAI_DECIMATION
-    episode_length_s = OPENAI_EPISODE_LENGTH_S
+    decimation = 3
+    episode_length_s = 8.0
     action_space = 20
     observation_space = 42
     state_space = 187
     asymmetric_obs = True
     obs_type = "openai"
     # simulation
-    sim: SimulationCfg = SimulationCfg(
-        dt=OPENAI_SIM_DT,
-        render_interval=decimation,
-        physics_material=RigidBodyMaterialCfg(static_friction=1.0, dynamic_friction=1.0),
-        physics=PhysicsCfg(),
-    )
+    sim: SimulationCfg = OPENAI_SIM_CFG
     # reset
-    reset_position_noise = OPENAI_RESET_POSITION_NOISE  # range of position at reset
-    reset_dof_pos_noise = OPENAI_RESET_DOF_POS_NOISE  # range of dof pos at reset
-    reset_dof_vel_noise = OPENAI_RESET_DOF_VEL_NOISE  # range of dof vel at reset
+    reset_position_noise = 0.01  # range of position at reset
+    reset_dof_pos_noise = 0.2  # range of dof pos at reset
+    reset_dof_vel_noise = 0.0  # range of dof vel at reset
     # reward scales
-    dist_reward_scale = OPENAI_DIST_REWARD_SCALE
-    rot_reward_scale = OPENAI_ROT_REWARD_SCALE
-    rot_eps = OPENAI_ROT_EPS
-    action_penalty_scale = OPENAI_ACTION_PENALTY_SCALE
-    reach_goal_bonus = OPENAI_REACH_GOAL_BONUS
-    fall_penalty = OPENAI_FALL_PENALTY
-    vel_obs_scale = OPENAI_VEL_OBS_SCALE
-    success_tolerance = OPENAI_SUCCESS_TOLERANCE
-    max_consecutive_success = OPENAI_MAX_CONSECUTIVE_SUCCESS
-    av_factor = OPENAI_AV_FACTOR
-    act_moving_average = OPENAI_ACT_MOVING_AVERAGE
-    force_torque_obs_scale = OPENAI_FORCE_TORQUE_OBS_SCALE
+    dist_reward_scale = -10.0
+    rot_reward_scale = 1.0
+    rot_eps = 0.1
+    action_penalty_scale = -0.0002
+    reach_goal_bonus = 250.0
+    fall_penalty = -50.0
+    vel_obs_scale = 0.2
+    success_tolerance = 0.4
+    max_consecutive_success = 50
+    av_factor = 0.1
+    act_moving_average = 0.3
+    force_torque_obs_scale = 10.0
     # domain randomization config
     events: ShadowHandEventCfg = ShadowHandEventCfg()
     # at every time-step add gaussian noise + bias. The bias is a gaussian sampled at reset