Unify physics randomization events across PhysX and Newton

source/isaaclab/config/extension.toml

@@ -1,7 +1,7 @@
 [package]
 
 # Note: Semantic Versioning is used: https://semver.org/
-version = "4.5.30"
+version = "4.5.31"
 
 # Description
 title = "Isaac Lab framework for Robot Learning"

source/isaaclab/docs/CHANGELOG.rst

@@ -1,6 +1,33 @@
 Changelog
 ---------
 
+4.5.31 (2026-04-13)
+~~~~~~~~~~~~~~~~~~~
+
+Added
+^^^^^
+
+* Added :class:`~isaaclab.envs.mdp.randomize_rigid_body_inertia` event term for
+  randomizing body inertia tensors independently of mass. Supports diagonal-only
+  (Ixx, Iyy, Izz) and full 3x3 modes.
+
+Changed
+^^^^^^^
+
+* Split :class:`~isaaclab.envs.mdp.randomize_rigid_body_material` into
+  backend-specific implementations. PhysX uses bucket-based 3-tuple materials via the
+  tensor API; Newton samples friction and restitution continuously per shape via
+  view-level attribute bindings.
+* Converted ``randomize_rigid_body_com`` from a plain function to a
+  :class:`~isaaclab.managers.ManagerTermBase` class with repeatable randomization
+  from cached defaults. Newton passes position-only (vec3); PhysX passes full pose
+  (pos + quat).
+* Converted ``randomize_rigid_body_collider_offsets`` from a plain function to a
+  :class:`~isaaclab.managers.ManagerTermBase` class with backend-specific
+  implementations. PhysX uses rest/contact offsets directly; Newton maps them to
+  ``shape_margin`` and ``shape_gap``.
+
+
 4.5.30 (2026-04-13)
 ~~~~~~~~~~~~~~~~~~~
 

source/isaaclab/isaaclab/envs/mdp/__init__.pyi

@@ -55,6 +55,7 @@ __all__ = [
     "randomize_physics_scene_gravity",
     "randomize_rigid_body_collider_offsets",
     "randomize_rigid_body_com",
+    "randomize_rigid_body_inertia",
     "randomize_rigid_body_mass",
     "randomize_rigid_body_material",
     "randomize_rigid_body_scale",
@@ -195,6 +196,7 @@ from .events import (
     randomize_physics_scene_gravity,
     randomize_rigid_body_collider_offsets,
     randomize_rigid_body_com,
+    randomize_rigid_body_inertia,
     randomize_rigid_body_mass,
     randomize_rigid_body_material,
     randomize_rigid_body_scale,

source/isaaclab_newton/config/extension.toml

@@ -1,7 +1,7 @@
 [package]
 
 # Note: Semantic Versioning is used: https://semver.org/
-version = "0.5.11"
+version = "0.5.12"
 
 # Description
 title = "Newton simulation interfaces for IsaacLab core package"

source/isaaclab_newton/docs/CHANGELOG.rst

@@ -1,6 +1,16 @@
 Changelog
 ---------
 
+0.5.12 (2026-04-13)
+~~~~~~~~~~~~~~~~~~~
+
+Added
+^^^^^
+
+* Added ``set_friction_index/mask`` and ``set_restitution_index/mask`` methods to
+  Newton assets for native material property randomization.
+
+
 0.5.11 (2026-04-13)
 ~~~~~~~~~~~~~~~~~~~
 
@@ -12,6 +22,7 @@ Added
   registration, wildcard body matching, and zero-copy transform views.
 
 
+
 0.5.10 (2026-04-05)
 ~~~~~~~~~~~~~~~~~~~
 

source/isaaclab_newton/test/assets/test_articulation.py

@@ -2487,5 +2487,122 @@ def _patched_simulate(cls):
         )
 
 
+@pytest.mark.parametrize("add_ground_plane", [True])
+@pytest.mark.parametrize("num_articulations", [1, 2])
+@pytest.mark.parametrize("device", ["cuda:0", "cpu"])
+@pytest.mark.parametrize("articulation_type", ["panda"])
+@pytest.mark.isaacsim_ci
+def test_set_material_properties(sim, num_articulations, device, add_ground_plane, articulation_type):
+    """Test getting and setting material properties (friction/restitution) via view-level APIs."""
+    articulation_cfg = generate_articulation_cfg(articulation_type=articulation_type)
+    articulation, _ = generate_articulation(
+        articulation_cfg=articulation_cfg, num_articulations=num_articulations, device=device
+    )
+
+    # Play the simulator
+    sim.reset()
+
+    # Get friction/restitution bindings via view-level API
+    model = SimulationManager.get_model()
+    friction_binding = articulation._root_view.get_attribute("shape_material_mu", model)[:, 0]
+    restitution_binding = articulation._root_view.get_attribute("shape_material_restitution", model)[:, 0]
+    num_shapes = friction_binding.shape[1]
+
+    # Test 1: Set all shapes via in-place writes to the warp binding
+    friction = torch.empty(num_articulations, num_shapes, device=device).uniform_(0.4, 0.8)
+    restitution = torch.empty(num_articulations, num_shapes, device=device).uniform_(0.0, 0.2)
+
+    wp.to_torch(friction_binding)[:] = friction
+    wp.to_torch(restitution_binding)[:] = restitution
+    SimulationManager.add_model_change(SolverNotifyFlags.SHAPE_PROPERTIES)
+
+    # Simulate physics
+    sim.step()
+    articulation.update(sim.cfg.dt)
+
+    # Verify by reading back from the binding
+    mu = wp.to_torch(friction_binding)
+    restitution_check = wp.to_torch(restitution_binding)
+    torch.testing.assert_close(mu, friction)
+    torch.testing.assert_close(restitution_check, restitution)
+
+    # Test 2: Set subset of shapes (only shape 0)
+    if num_shapes > 1:
+        subset_friction = torch.empty(num_articulations, device=device).uniform_(0.1, 0.2)
+        subset_restitution = torch.empty(num_articulations, device=device).uniform_(0.5, 0.6)
+
+        wp.to_torch(friction_binding)[:, 0] = subset_friction
+        wp.to_torch(restitution_binding)[:, 0] = subset_restitution
+        SimulationManager.add_model_change(SolverNotifyFlags.SHAPE_PROPERTIES)
+
+        sim.step()
+        articulation.update(sim.cfg.dt)
+
+        # Check only the subset was updated
+        mu_updated = wp.to_torch(friction_binding)
+        restitution_updated = wp.to_torch(restitution_binding)
+        torch.testing.assert_close(mu_updated[:, 0], subset_friction)
+        torch.testing.assert_close(restitution_updated[:, 0], subset_restitution)
+
+
+@pytest.mark.parametrize("num_articulations", [2])
+@pytest.mark.parametrize("device", ["cuda:0"])
+@pytest.mark.parametrize("add_ground_plane", [True])
+@pytest.mark.parametrize("articulation_type", ["anymal"])
+@pytest.mark.isaacsim_ci
+def test_randomize_rigid_body_com(sim, num_articulations, device, add_ground_plane, articulation_type):
+    """Test that randomize_rigid_body_com modifies CoM and affects simulation dynamics."""
+    articulation_cfg = generate_articulation_cfg(articulation_type=articulation_type)
+    articulation, _ = generate_articulation(articulation_cfg, num_articulations, device=device)
+
+    sim.reset()
+    assert articulation.is_initialized
+
+    original_com = wp.to_torch(articulation.data.body_com_pos_b).clone()
+
+    com_offset = torch.zeros(num_articulations, articulation.num_bodies, 3, device=device)
+    com_offset[..., 0] = 0.5
+    new_com = original_com + com_offset
+    env_ids = torch.arange(num_articulations, device=device, dtype=torch.int32)
+    articulation.set_coms_index(coms=new_com, env_ids=env_ids)
+
+    updated_com = wp.to_torch(articulation.data.body_com_pos_b)
+    torch.testing.assert_close(updated_com, new_com, atol=1e-5, rtol=1e-5)
+
+
+@pytest.mark.parametrize("num_articulations", [2])
+@pytest.mark.parametrize("device", ["cuda:0"])
+@pytest.mark.parametrize("add_ground_plane", [True])
+@pytest.mark.parametrize("articulation_type", ["anymal"])
+@pytest.mark.isaacsim_ci
+def test_randomize_rigid_body_collider_offsets(sim, num_articulations, device, add_ground_plane, articulation_type):
+    """Test that Newton collider offset randomization (shape_margin, shape_gap) takes effect."""
+    articulation_cfg = generate_articulation_cfg(articulation_type=articulation_type)
+    articulation, _ = generate_articulation(articulation_cfg, num_articulations, device=device)
+
+    sim.reset()
+    assert articulation.is_initialized
+
+    model = SimulationManager.get_model()
+    original_margin = wp.to_torch(articulation.root_view.get_attribute("shape_margin", model)).clone()
+    original_gap = wp.to_torch(articulation.root_view.get_attribute("shape_gap", model)).clone()
+
+    new_margin = original_margin.clone()
+    new_margin[:, 0] += 0.01
+    articulation.root_view.set_attribute("shape_margin", model, wp.from_torch(new_margin, dtype=wp.float32))
+
+    new_gap = original_gap.clone()
+    new_gap[:, 0] += 0.005
+    articulation.root_view.set_attribute("shape_gap", model, wp.from_torch(new_gap, dtype=wp.float32))
+
+    with wp.ScopedDevice(device):
+        SimulationManager._solver.notify_model_changed(SolverNotifyFlags.SHAPE_PROPERTIES)
+
+    updated_margin = wp.to_torch(articulation.root_view.get_attribute("shape_margin", model))
+    updated_gap = wp.to_torch(articulation.root_view.get_attribute("shape_gap", model))
+    torch.testing.assert_close(updated_margin, new_margin)
+    torch.testing.assert_close(updated_gap, new_gap)
+
+
 if __name__ == "__main__":
     pytest.main([__file__, "-v", "--maxfail=1"])