Add Newton physics backend support

.github/workflows/main.yml

@@ -75,7 +75,7 @@ jobs:
       - name: Build docs
         shell: bash
         run: |
-          pip install -e . --extra-index-url http://pyp.open3dv.site:2345/simple/ --trusted-host pyp.open3dv.site
+          pip install -e . --extra-index-url http://pyp.open3dv.site:2345/simple/ --trusted-host pyp.open3dv.site 
           pip install -r docs/requirements.txt
           python3 docs/scripts/sync_readme.py
           cd ${GITHUB_WORKSPACE}/docs

embodichain/lab/gym/envs/base_env.py

@@ -129,9 +129,7 @@ def __init__(
 
         self._setup_scene(**kwargs)
 
-        # TODO: To be removed.
-        if self.device.type == "cuda":
-            self.sim.init_gpu_physics()
+        self.sim.prepare_physics()
 
         if not self.sim_cfg.headless:
             self.sim.open_window()

embodichain/lab/sim/cfg.py

@@ -77,7 +77,7 @@ def to_dexsim_flags(self):
 
 
 @configclass
-class PhysicsCfg:
+class DefaultPhysicsCfg:
     gravity: np.ndarray = field(default_factory=lambda: np.array([0, 0, -9.81]))
     """Gravity vector for the simulation environment."""
 
@@ -124,6 +124,95 @@ def to_dexsim_args(self) -> Dict[str, Any]:
         return args
 
 
+# Backwards-compatible alias for existing task configs.
+PhysicsCfg = DefaultPhysicsCfg
+
+
+@configclass
+class NewtonPhysicsCfg:
+    """Configuration for DexSim Newton physics backend."""
+
+    num_substeps: int = 10
+    """Number of Newton solver substeps per EmbodiChain physics step."""
+
+    device: str | None = None
+    """Newton device. If None, derived from ``SimulationManagerCfg.sim_device`` and ``gpu_id``."""
+
+    require_grad: bool = False
+    """Whether to finalize the Newton model for differentiable simulation."""
+
+    use_cuda_graph: bool = True
+    """Whether to use CUDA graph capture for Newton stepping when supported."""
+
+    debug_mode: bool = False
+    """Whether to enable Newton debug mode."""
+
+    solver_type: Literal["mjwarp", "xpbd", "semi_implicit", "featherstone", "vbd"] = (
+        "semi_implicit"
+    )
+    """Newton solver preset."""
+
+    broad_phase: Literal["nxn", "sap", "explicit"] | None = None
+    """Newton collision broad-phase implementation. If None, DexSim chooses its default."""
+
+    visualizer_enabled: bool = False
+    """Whether to enable the Newton visualizer."""
+
+    def to_dexsim_cfg(
+        self,
+        physics_dt: float,
+        sim_device: str | torch.device,
+        gpu_id: int,
+    ):
+        """Convert this config to ``dexsim.engine.newton_physics.NewtonCfg``."""
+        from dexsim.engine.newton_physics import (
+            FeatherstoneSolverCfg,
+            MJWarpSolverCfg,
+            NewtonCfg,
+            NewtonCollisionPipelineCfg,
+            SemiImplicitSolverCfg,
+            VBDSolverCfg,
+            XPBDSolverCfg,
+        )
+
+        torch_device = (
+            torch.device(sim_device) if isinstance(sim_device, str) else sim_device
+        )
+        device = self.device
+        if device is None:
+            device = f"cuda:{gpu_id}" if torch_device.type == "cuda" else "cpu"
+
+        solver_cfg_map = {
+            "mjwarp": MJWarpSolverCfg,
+            "xpbd": XPBDSolverCfg,
+            "semi_implicit": SemiImplicitSolverCfg,
+            "featherstone": FeatherstoneSolverCfg,
+            "vbd": VBDSolverCfg,
+        }
+        solver_cfg = solver_cfg_map[self.solver_type]()
+
+        if self.require_grad and self.solver_type != "semi_implicit":
+            logger.log_error(
+                "Newton gradient mode requires solver_type='semi_implicit'."
+            )
+
+        cfg = NewtonCfg(
+            dt=physics_dt,
+            num_substeps=self.num_substeps,
+            device=device,
+            debug_mode=self.debug_mode,
+            require_grad=self.require_grad,
+            solver_cfg=solver_cfg,
+            collision_pipeline_cfg=NewtonCollisionPipelineCfg(
+                broad_phase=self.broad_phase,
+                requires_grad=self.require_grad,
+            ),
+        )
+        cfg.use_cuda_graph = self.use_cuda_graph and not self.require_grad
+        cfg._visualizer_enabled = self.visualizer_enabled
+        return cfg
+
+
 @configclass
 class MarkerCfg:
     """Configuration for visual markers in the simulation.

embodichain/lab/sim/objects/backends/__init__.py

@@ -0,0 +1,26 @@
+# ----------------------------------------------------------------------------
+# Copyright (c) 2021-2026 DexForce Technology Co., Ltd.
+#
+# Licensed under the Apache License, Version 2.0 (the "License");
+# you may not use this file except in compliance with the License.
+# You may obtain a copy of the License at
+#
+#     http://www.apache.org/licenses/LICENSE-2.0
+#
+# Unless required by applicable law or agreed to in writing, software
+# distributed under the License is distributed on an "AS IS" BASIS,
+# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
+# See the License for the specific language governing permissions and
+# limitations under the License.
+# ----------------------------------------------------------------------------
+
+from .base import RigidBodyViewBase
+from .default import DefaultRigidBodyView
+from .newton import NewtonRigidBodyView, is_newton_scene
+
+__all__ = [
+    "RigidBodyViewBase",
+    "DefaultRigidBodyView",
+    "NewtonRigidBodyView",
+    "is_newton_scene",
+]

embodichain/lab/sim/objects/backends/base.py

@@ -0,0 +1,128 @@
+# ----------------------------------------------------------------------------
+# Copyright (c) 2021-2026 DexForce Technology Co., Ltd.
+#
+# Licensed under the Apache License, Version 2.0 (the "License");
+# you may not use this file except in compliance with the License.
+# You may obtain a copy of the License at
+#
+#     http://www.apache.org/licenses/LICENSE-2.0
+#
+# Unless required by applicable law or agreed to in writing, software
+# distributed under the License is distributed on an "AS IS" BASIS,
+# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
+# See the License for the specific language governing permissions and
+# limitations under the License.
+# ----------------------------------------------------------------------------
+from __future__ import annotations
+
+from abc import ABC, abstractmethod
+from typing import Sequence
+
+import torch
+
+__all__ = ["RigidBodyViewBase"]
+
+
+class RigidBodyViewBase(ABC):
+    """Abstract interface for physics-backend rigid body data access.
+
+    All pose/velocity/acceleration data uses EmbodiChain convention:
+    ``(x, y, z, qx, qy, qz, qw)``.
+    """
+
+    # -- Lifecycle & State --------------------------------------------------
+
+    @property
+    @abstractmethod
+    def is_ready(self) -> bool:
+        """Whether the backend simulation is finalized and data can be accessed."""
+        ...
+
+    # -- Body ID Management -------------------------------------------------
+
+    @property
+    @abstractmethod
+    def body_ids(self) -> list[int]:
+        """Backend body IDs for all managed entities."""
+        ...
+
+    @property
+    @abstractmethod
+    def body_ids_tensor(self) -> torch.Tensor:
+        """Body IDs as an int32 tensor on ``device``."""
+        ...
+
+    @abstractmethod
+    def select_body_ids(self, indices: Sequence[int] | torch.Tensor) -> list[int]:
+        """Return body IDs for the given entity indices."""
+        ...
+
+    # -- Pose ---------------------------------------------------------------
+
+    @abstractmethod
+    def fetch_pose(self, body_ids: Sequence[int] | None = None) -> torch.Tensor:
+        """Fetch poses as ``(N, 7)`` tensor in ``(x, y, z, qx, qy, qz, qw)``."""
+        ...
+
+    @abstractmethod
+    def apply_pose(self, pose: torch.Tensor, body_ids: Sequence[int]) -> None:
+        """Apply poses from ``(N, 7)`` tensor in ``(x, y, z, qx, qy, qz, qw)``."""
+        ...
+
+    # -- Velocity -----------------------------------------------------------
+
+    @abstractmethod
+    def fetch_linear_velocity(
+        self, body_ids: Sequence[int] | None = None
+    ) -> torch.Tensor:
+        """Fetch linear velocities as ``(N, 3)`` tensor."""
+        ...
+
+    @abstractmethod
+    def fetch_angular_velocity(
+        self, body_ids: Sequence[int] | None = None
+    ) -> torch.Tensor:
+        """Fetch angular velocities as ``(N, 3)`` tensor."""
+        ...
+
+    @abstractmethod
+    def apply_linear_velocity(
+        self, data: torch.Tensor, body_ids: Sequence[int]
+    ) -> None:
+        """Set linear velocities from ``(N, 3)`` tensor."""
+        ...
+
+    @abstractmethod
+    def apply_angular_velocity(
+        self, data: torch.Tensor, body_ids: Sequence[int]
+    ) -> None:
+        """Set angular velocities from ``(N, 3)`` tensor."""
+        ...
+
+    # -- Acceleration -------------------------------------------------------
+
+    @abstractmethod
+    def fetch_linear_acceleration(
+        self, body_ids: Sequence[int] | None = None
+    ) -> torch.Tensor:
+        """Fetch linear accelerations as ``(N, 3)`` tensor."""
+        ...
+
+    @abstractmethod
+    def fetch_angular_acceleration(
+        self, body_ids: Sequence[int] | None = None
+    ) -> torch.Tensor:
+        """Fetch angular accelerations as ``(N, 3)`` tensor."""
+        ...
+
+    # -- Force & Torque -----------------------------------------------------
+
+    @abstractmethod
+    def apply_force(self, data: torch.Tensor, body_ids: Sequence[int]) -> None:
+        """Apply external forces ``(N, 3)``.  One-shot — consumed on next step."""
+        ...
+
+    @abstractmethod
+    def apply_torque(self, data: torch.Tensor, body_ids: Sequence[int]) -> None:
+        """Apply external torques ``(N, 3)``.  One-shot — consumed on next step."""
+        ...