[Newton] Fixes contact sensor metadata access

source/isaaclab_newton/changelog.d/ca-fix-newton-contact-sensor-migration.rst

@@ -0,0 +1,7 @@
+Fixed
+^^^^^
+
+* Fixed :class:`~isaaclab_newton.sensors.ContactSensor` metadata extraction
+  after the migration to Newton 1.1, where ``sensing_obj_type`` and
+  ``counterpart_type`` became scalar strings and ``counterpart_indices``
+  became per-row.

source/isaaclab_newton/isaaclab_newton/sensors/contact_sensor/contact_sensor.py

@@ -346,48 +346,42 @@ def _create_buffers(self):
         body_labels = self._get_model_labels("body")
         shape_labels = self._get_model_labels("shape")
 
-        def get_name(idx, kind):
-            kind_name = getattr(kind, "name", None)
-            kind_value = getattr(kind, "value", kind)
-            if kind_name == "BODY" or kind_value == 2:
-                return body_labels[int(idx)].split("/")[-1]
-            if kind_name == "SHAPE" or kind_value == 1:
-                return shape_labels[int(idx)].split("/")[-1]
-            return "MATCH_ANY"
-
-        def flatten_metadata(values):
-            if isinstance(values, wp.array):
-                values = values.numpy()
-            flat_values = np.asarray(values, dtype=object).reshape(-1).tolist()
-            if flat_values and isinstance(flat_values[0], list | tuple | np.ndarray):
-                return [
-                    value
-                    for nested_values in flat_values
-                    for value in np.asarray(nested_values, dtype=object).reshape(-1).tolist()
-                ]
-            return flat_values
-
-        flat_sensing = list(
-            zip(
-                flatten_metadata(self.contact_view.sensing_obj_idx),
-                flatten_metadata(self.contact_view.sensing_obj_type),
-            )
-        )
-        self._sensor_names = [get_name(idx, kind) for idx, kind in flat_sensing]
+        s_kind = self.contact_view.sensing_obj_type
+        if s_kind == "body":
+            s_labels = body_labels
+        elif s_kind == "shape":
+            s_labels = shape_labels
+        else:
+            raise RuntimeError(f"Unexpected Newton sensing_obj_type {s_kind!r}; expected 'body' or 'shape'.")
+        self._sensor_names = [s_labels[i].split("/")[-1] for i in self.contact_view.sensing_obj_idx]
         # Assumes the environments are processed in order.
         self._sensor_names = self._sensor_names[: self._num_sensors]
-        flat_counterparts = list(
-            zip(
-                flatten_metadata(self.contact_view.counterpart_indices),
-                flatten_metadata(self.contact_view.counterpart_type),
-            )
-        )
-        self._filter_object_names = [get_name(idx, kind) for idx, kind in flat_counterparts]
+
+        c_kind = self.contact_view.counterpart_type
+        c_idx_per_sensor = self.contact_view.counterpart_indices
+        if c_kind is None:
+            if self._generate_force_matrix:
+                raise RuntimeError("Filter expressions were configured but Newton reports no counterpart type.")
+            self._filter_object_names = []
+        else:
+            if c_kind == "body":
+                c_labels = body_labels
+            elif c_kind == "shape":
+                c_labels = shape_labels
+            else:
+                raise RuntimeError(f"Unexpected Newton counterpart_type {c_kind!r}; expected 'body' or 'shape'.")
+            # Envs are homogeneous: every sensor row sees the same counterpart list. Take row 0.
+            row0 = c_idx_per_sensor[0] if c_idx_per_sensor else []
+            self._filter_object_names = [c_labels[i].split("/")[-1] for i in row0]
+            if self._generate_force_matrix and not self._filter_object_names:
+                logger.warning("Filter expressions matched zero counterpart objects; force matrix will be empty.")
 
         force_matrix = self.contact_view.force_matrix
         force_matrix_shape = force_matrix.shape if force_matrix is not None else (total_sensor_count, 0)
         # Number of filter objects.
         self._num_filter_objects = force_matrix_shape[1] if len(force_matrix_shape) > 1 else 0
+        if self._num_filter_objects > 0 and force_matrix is None:
+            raise RuntimeError("Filter counterparts present but Newton force_matrix is None.")
 
         # Store flat Newton force views for copying data. These may be non-contiguous
         # views, so the copy kernel indexes them without reshaping.

source/isaaclab_newton/test/sensors/test_contact_sensor.py

@@ -26,6 +26,7 @@
 
 import pytest
 import torch
+from isaaclab_newton.sensors.contact_sensor import ContactSensorCfg as NewtonContactSensorCfg
 from physics.physics_test_utils import (
     COLLISION_PIPELINES,
     STABLE_SHAPES,
@@ -780,6 +781,112 @@ def test_finger_contact_sensor_isolation(device: str, use_mujoco_contacts: bool,
                     )
 
 
+# ===================================================================
+# Sensor metadata
+# ===================================================================
+
+
+def _make_two_box_scene_cfg(num_envs: int) -> ContactSensorTestSceneCfg:
+    """Scene with two distinct Cuboid bodies (BoxA, BoxB) per env."""
+    rigid_props = sim_utils.RigidBodyPropertiesCfg(disable_gravity=True, linear_damping=0.0, angular_damping=0.0)
+    scene_cfg = ContactSensorTestSceneCfg(num_envs=num_envs, env_spacing=5.0, lazy_sensor_update=False)
+    scene_cfg.object_a = RigidObjectCfg(
+        prim_path="{ENV_REGEX_NS}/BoxA",
+        spawn=sim_utils.CuboidCfg(
+            size=(0.3, 0.3, 0.3),
+            rigid_props=rigid_props,
+            collision_props=sim_utils.CollisionPropertiesCfg(collision_enabled=True),
+            mass_props=sim_utils.MassPropertiesCfg(mass=1.0),
+            activate_contact_sensors=True,
+        ),
+        init_state=RigidObjectCfg.InitialStateCfg(pos=(-0.5, 0.0, 1.0)),
+    )
+    scene_cfg.object_b = RigidObjectCfg(
+        prim_path="{ENV_REGEX_NS}/BoxB",
+        spawn=sim_utils.CuboidCfg(
+            size=(0.3, 0.3, 0.3),
+            rigid_props=rigid_props,
+            collision_props=sim_utils.CollisionPropertiesCfg(collision_enabled=True),
+            mass_props=sim_utils.MassPropertiesCfg(mass=1.0),
+            activate_contact_sensors=True,
+        ),
+        init_state=RigidObjectCfg.InitialStateCfg(pos=(0.5, 0.0, 1.0)),
+    )
+    return scene_cfg
+
+
+@pytest.mark.parametrize("device", ["cuda:0", "cpu"])
+def test_sensor_metadata(device: str):
+    """Verify sensor_names and filter_object_names match the underlying sensing and
+    counterpart configuration across body-mode, body-mode-with-filter, and shape-mode.
+    """
+    num_envs = 4
+    sim_cfg = make_sim_cfg(use_mujoco_contacts=False, device=device, gravity=(0.0, 0.0, -9.81))
+
+    # (1) Body-mode, no filter: pattern matches two distinct body names per env.
+    with build_simulation_context(sim_cfg=sim_cfg, auto_add_lighting=True, add_ground_plane=True) as sim:
+        sim._app_control_on_stop_handle = None
+        scene_cfg = _make_two_box_scene_cfg(num_envs)
+        scene_cfg.contact_sensor_a = ContactSensorCfg(
+            prim_path="{ENV_REGEX_NS}/Box.*",
+            update_period=0.0,
+            history_length=1,
+        )
+        scene = InteractiveScene(scene_cfg)
+        sim.reset()
+        scene.reset()
+
+        sensor: ContactSensor = scene["contact_sensor_a"]
+        assert sensor.num_sensors == 2, f"expected 2 sensors per env, got {sensor.num_sensors}"
+        assert sensor.sensor_names == ["BoxA", "BoxB"], f"unexpected sensor_names: {sensor.sensor_names}"
+        assert sensor.filter_object_names == [], (
+            f"expected empty filter_object_names with no filter, got {sensor.filter_object_names}"
+        )
+
+    # (2) Body-mode, with filter: one body matches the sensor pattern, one matches the filter pattern.
+    with build_simulation_context(sim_cfg=sim_cfg, auto_add_lighting=True, add_ground_plane=True) as sim:
+        sim._app_control_on_stop_handle = None
+        scene_cfg = _make_two_box_scene_cfg(num_envs)
+        scene_cfg.contact_sensor_a = ContactSensorCfg(
+            prim_path="{ENV_REGEX_NS}/BoxA",
+            filter_prim_paths_expr=["{ENV_REGEX_NS}/BoxB"],
+            update_period=0.0,
+            history_length=1,
+        )
+        scene = InteractiveScene(scene_cfg)
+        sim.reset()
+        scene.reset()
+
+        sensor: ContactSensor = scene["contact_sensor_a"]
+        assert sensor.num_sensors == 1, f"expected 1 sensor per env, got {sensor.num_sensors}"
+        assert sensor.sensor_names == ["BoxA"], f"unexpected sensor_names: {sensor.sensor_names}"
+        assert sensor.num_filter_objects == 1, f"expected 1 filter object per sensor, got {sensor.num_filter_objects}"
+        assert sensor.filter_object_names == ["BoxB"], f"unexpected filter_object_names: {sensor.filter_object_names}"
+
+    # (3) Shape-mode, no filter: pattern matches shapes (not bodies).
+    # `sensor_shape_prim_expr` is a Newton-only extension, so this block uses the
+    # backend-specific NewtonContactSensorCfg subclass.
+    with build_simulation_context(sim_cfg=sim_cfg, auto_add_lighting=True, add_ground_plane=True) as sim:
+        sim._app_control_on_stop_handle = None
+        scene_cfg = _make_two_box_scene_cfg(num_envs)
+        scene_cfg.contact_sensor_a = NewtonContactSensorCfg(
+            prim_path="{ENV_REGEX_NS}/Box.*",
+            sensor_shape_prim_expr=["{ENV_REGEX_NS}/Box.*"],
+            update_period=0.0,
+            history_length=1,
+        )
+        scene = InteractiveScene(scene_cfg)
+        sim.reset()
+        scene.reset()
+
+        sensor: ContactSensor = scene["contact_sensor_a"]
+        assert sensor.num_sensors == 2, f"expected 2 shape sensors per env, got {sensor.num_sensors}"
+        assert sensor.sensor_names == ["mesh", "mesh"], f"unexpected shape sensor_names: {sensor.sensor_names}"
+        assert sensor.filter_object_names == [], (
+            f"expected empty filter_object_names with no filter, got {sensor.filter_object_names}"
+        )
+
+
 # ===================================================================
 # Utility
 # ===================================================================