OvPhysX#
Warning
Do not combine OvPhysX with the Kit visualizer. Commands such as
physics=ovphysx --visualizer kit are unsupported because ovphysx
loads USD-dependent PhysX plugins from its own package, while Kit already
owns a separate USD/plugin stack in the same process. Use
--visualizer newton_gl, --visualizer rerun, --visualizer viser,
or omit --visualizer for headless execution.
OvPhysX runs PhysX without Omniverse Kit. It reads scene-level solver settings
from the USD PhysicsScene prim. OvPhysxCfg holds
GPU buffer settings that USD does not represent.
OvPhysX is selected through OvPhysxCfg:
from isaaclab.sim import SimulationCfg
from isaaclab_ov.physics import OvPhysxCfg
sim_cfg = SimulationCfg(physics=OvPhysxCfg())
Why use OvPhysX?#
No Kit runtime. Run headless simulations without Isaac Sim.
USD configuration. Scene-authoring tools can set solver parameters directly on the
PhysicsSceneprim.
What works today#
OvPhysX supports the following components. The notes describe requirements and limits to consider when configuring a task.
Component |
Coverage and limits |
|---|---|
Rigid objects and articulations |
Rigid objects, rigid-object collections, and articulations. |
Contact sensing |
Aggregate and filtered forces, contact points, and contact timing. Pose tracking requires one sensor body per environment. |
Motion and frame sensing |
IMU, PVA, and frame transforms. Joint-wrench readings include the root body and use the child-side joint frame. |
Ray casting |
Ray casters and ray-cast cameras using Warp meshes. The standard ray caster requires static target meshes. |
Rendering and scene data |
Scene-data and frame-view implementations support kit-less consumers, including OVRTX. Isaac Sim / Kit cannot share the process. |
Deformables |
Volume and surface deformables on CUDA. Bodies in one view need matching node counts; see Deformable limitations. |
Heterogeneous cloning |
Geometry variants with matching body, joint, and tendon layouts; see Heterogeneous cloning. |
See Sensors for sensor configuration and Renderers for renderer choices.
Installation#
The ovphysx extra requires OvPhysX 0.6.4.72118723. Install it from the repository root with:
uv sync --inexact --extra ovphysx
The --inexact flag preserves packages installed through other extras.
Use --extra ov to install both public OvPhysX and OVRTX runtimes. The combined
extra pairs OVRTX 0.5.1.385782 with OVStage 0.2.1; OVRTX 0.4.1 is not compatible
with this runtime combination. The legacy
Isaac Lab installer also supports ./isaaclab.sh -i 'ov[ovphysx]' and
./isaaclab.sh -i 'ov[all]'.
Testing the Installation#
First check that the Python package and runtime wheel import correctly:
uv run --extra ovphysx --extra test python -c "import ovphysx.types; from isaaclab_ov.physics import OvPhysxCfg; print('OvPhysX runtime OK')"
./isaaclab.sh -p -c "import ovphysx.types; from isaaclab_ov.physics import OvPhysxCfg; print('OvPhysX runtime OK')"
Then run a small backend smoke test:
uv run --extra ovphysx --extra test python -m pytest source/isaaclab_ov/test/assets/test_rigid_object.py::test_initialization -k cpu
./isaaclab.sh -p -m pytest source/isaaclab_ov/test/assets/test_rigid_object.py::test_initialization -k cpu
To try a task that declares an OvPhysX physics preset, use the same preset CLI syntax as the other backends:
uv run --extra ovphysx isaaclab zero_agent --task Isaac-Cartpole-Direct \
--num_envs 128 --max_steps 64 --viz none physics=ovphysx
./isaaclab.sh -p scripts/environments/zero_agent.py --task Isaac-Cartpole-Direct \
--num_envs 128 --max_steps 64 --viz none physics=ovphysx
This command runs a 64-step headless zero-action rollout and then exits.
Supported locomotion environments#
Use the environment browser or task help
for the available physics= presets. To list launchable combinations:
uv run --extra ovphysx isaaclab list_envs --show_presets --keyword Velocity
Playback uses the same physics=ovphysx selector as training.
Locomotion task examples
Isaac-Ant-DirectIsaac-Humanoid-DirectIsaacContrib-Velocity-Rough-AnymalBIsaacContrib-Velocity-Rough-AnymalCIsaac-Velocity-Flat-AnymalDIsaac-Velocity-Rough-AnymalDIsaacContrib-Velocity-Rough-UnitreeA1IsaacContrib-Velocity-Rough-UnitreeGo1Isaac-Velocity-Rough-UnitreeGo2Isaac-Velocity-Rough-CassieIsaac-Velocity-Rough-G1Isaac-Velocity-Rough-H1
Heterogeneous cloning#
OvPhysX 0.6.3 is required for heterogeneous runtime cloning. Tensor bindings use numeric environment order so indexed resets, actions and observations address the correct variant. Variants may differ in geometry but must preserve body, joint and tendon layout. Isaac Lab checks prototype rotation axes and tendon layouts; OVPhysX checks body and joint metadata when binding articulations.
The clone context compiles the plan’s prototypes and world assignments once. The physics manager attaches one exported stage, replays the native copies, and warms the runtime before assets and sensors bind. Hard reset reuses the same declarations; there is no separate consumable queue. Binding paths come from the plan’s world layout and environment template, not from native clone order.
Authored sources all receive native environment ID zero. Every world containing a source or USD-only physics therefore imports all its declared assets as originals. Other worlds clone their assets from a complete original world of the same composition, using one native environment ID per destination world. This keeps a robot, table and object able to contact one another without destination placeholders. Only declared asset subtrees are copied; unrelated authored assets are retained.
Keep filter_collisions enabled to
isolate original worlds with USD collision groups. GPU copies additionally use
native environment-ID filtering. CPU has no native environment-ID filtering
in OvPhysX 0.6.3, so it imports all declared USD copies and uses collision groups.
Large overlapping original layouts can still exhaust broadphase pair capacity;
use spatially separated environments.
Deformable limitations#
OvPhysX deformables currently require every body matched by one
DeformableObject to have the same number of simulation
nodes. Initialization raises an error for mixed node counts instead of exposing
padded state that would produce incorrect reductions.
Deformable scenes also require full-stage materialization. Startup cost therefore grows with the number of authored environments. Use this path for small validation scenes; training-scale workloads with thousands of environments are not currently supported. Deformable bodies are not supported by the heterogeneous fast-path cloner.
Native access#
Use native access when the shared asset and sensor APIs do not expose the data or operation you need. Reuse an Isaac Lab-owned handle when its selection matches; create raw access only for additional capabilities. Native writes can bypass Isaac Lab’s caches and validation, so follow the ownership and synchronization rules below.
Mental model#
OvPhysX exposes generic TensorBinding objects. A binding combines a prim
selection with one installed TensorType; it is not an asset-specific native
storage object. Callers explicitly pull values into their own buffer with
read() and push a buffer back with write(). Isaac Lab optionally wraps
these bindings in OvPhysxView for a
string-keyed, guarded convenience surface.
Lifecycle prerequisite#
Create bindings only after the OvPhysX simulation has initialized and reset, when its native runtime is live. A stage reload, a reset path that rebuilds the stage or runtime, and manager teardown invalidate all existing bindings and views. Reacquire them afterwards.
Get the active OvPhysX handle from the manager after the lifecycle prerequisite:
from isaaclab_ov.physics import OvPhysxManager
physx = OvPhysxManager.get_physx_instance()
if physx is None:
raise RuntimeError("OvPhysX has not been constructed; initialize and reset the simulation first.")
A non-None handle proves only that the manager constructed an OvPhysX instance; it is not a
readiness predicate for the current simulation context. Manager teardown releases the instance
and clears this handle. Initialize and reset the current context before access, and always
reacquire the handle before creating new bindings or views.
Reuse Isaac Lab-owned access#
Reuse the convenience view already owned by an Isaac Lab asset when its selection matches:
object_view = scene["object"].root_view
poses = object_view.get_attribute("rigid_body_pose")
Create raw access#
Create a raw binding when the desired selection is not already owned by an Isaac Lab asset. The following representative pose binding is float32 and uses the simulation device; it is not a generic allocator for every tensor type:
import warp as wp
from isaaclab.physics import PhysicsManager
from ovphysx.types import TensorType
binding = physx.create_tensor_binding(
pattern="/World/envs/env_*/Object",
tensor_type=TensorType.RIGID_BODY_POSE,
)
try:
poses = wp.empty(
tuple(binding.shape),
dtype=wp.float32,
device=PhysicsManager.get_device(),
)
binding.read(poses)
binding.write(poses)
finally:
binding.destroy()
Before allocating a buffer, inspect binding.shape, binding.dtype, the
binding’s count, and its path metadata. Match the binding shape and DLPack scalar
metadata exactly, and respect the binding’s native device and access mode.
RIGID_BODY_POSE has the float32 layout used above, but another tensor type
can have a different scalar dtype, shape, native device, or write permission.
For a new selection, construct OvPhysxView
with the native runtime and a Tensor API pattern:
from isaaclab.physics import PhysicsManager
from isaaclab_ov.sim.views import OvPhysxView
view = OvPhysxView(
physx,
pattern="/World/envs/env_*/Object",
device=PhysicsManager.get_device(),
)
try:
if view.try_binding_for("rigid_body_pose") is not None:
poses = view.get_attribute("rigid_body_pose")
view.set_attribute("rigid_body_pose", poses)
view.read_into("rigid_body_pose", poses)
finally:
view.close()
try_binding_for attempts to create a binding for this selection and returns
None when a valid type is unavailable. binding_for returns a raw binding
and bypasses the view’s device, dtype, shape, and read-only guards.
Read/write semantics#
Raw binding.read(buffer) calls pull values into caller-owned buffers, while
binding.write(buffer) calls push values to the simulation. Editing a local
buffer alone does not change the simulation. The guarded
get_attribute(),
read_into(), and
set_attribute() paths provide the
same pull/push boundary while validating the binding’s shape, scalar dtype,
native device, and writable access.
Ownership, synchronization, and invalidation#
Allocate buffers on the binding’s required device and match its shape and
DLPack scalar metadata. State tensors normally use the simulation device, while
some property tensors are CPU-only. OvPhysxView
validates these requirements and can reinterpret supported flat scalar layouts
as structured Warp values, but it does not move data between CPU and GPU.
Use try_binding_for when a tensor type might not apply to the selected
prims. Reacquire raw bindings and convenience views after reset paths that
rebuild the stage or runtime, or after teardown. Destroy raw bindings and close
custom views before they are no longer needed. Manager teardown closes tracked
OvPhysxView instances before releasing the runtime, but explicit cleanup
avoids retaining their bindings for the rest of a long-lived simulation.
Where to go next#
Environments — tasks and backend presets.
Backend architecture — shared factories and resource ownership.
Scene Data Provider — shared scene data for renderers and visualizers.