Fixed visual prims handling during texture randomization.

source/isaaclab/config/extension.toml

@@ -1,7 +1,7 @@
 [package]
 
 # Note: Semantic Versioning is used: https://semver.org/
-version = "0.40.5"
+version = "0.40.6"
 
 # Description
 title = "Isaac Lab framework for Robot Learning"

source/isaaclab/docs/CHANGELOG.rst

@@ -1,6 +1,15 @@
 Changelog
 ---------
 
+0.40.6 (2025-06-12)
+~~~~~~~~~~~~~~~~~~~
+
+Fixed
+^^^^^
+
+* Fixed potential issues in :func:`~isaaclab.envs.mdp.events.randomize_visual_texture_material` related to handling visual prims during texture randomization.
+
+
 0.40.5 (2025-05-22)
 ~~~~~~~~~~~~~~~~~~~
 

source/isaaclab/isaaclab/envs/mdp/events.py

@@ -1229,8 +1229,25 @@ def __init__(self, cfg: EventTermCfg, env: ManagerBasedEnv):
             body_names_regex = ".*"
 
         # create the affected prim path
-        # TODO: Remove the hard-coded "/visuals" part.
-        prim_path = f"{asset.cfg.prim_path}/{body_names_regex}/visuals"
+        # Check if the pattern with '/visuals' yields results when matching `body_names_regex`.
+        # If not, fall back to a broader pattern without '/visuals'.
+        asset_main_prim_path = asset.cfg.prim_path
+        # Try the pattern with '/visuals' first for the generic case
+        pattern_with_visuals = f"{asset_main_prim_path}/{body_names_regex}/visuals"
+        # Use sim_utils to check if any prims currently match this pattern
+        matching_prims = sim_utils.find_matching_prim_paths(pattern_with_visuals)
+        if matching_prims:
+            # If matches are found, use the pattern with /visuals
+            prim_path = pattern_with_visuals
+        else:
+            # If no matches found, fall back to the broader pattern without /visuals
+            # This pattern (e.g., /World/envs/env_.*/Table/.*) should match visual prims
+            # whether they end in /visuals or have other structures.
+            prim_path = f"{asset_main_prim_path}/.*"
+            carb.log_info(
+                f"Pattern '{pattern_with_visuals}' found no prims. Falling back to '{prim_path}' for texture"
+                " randomization."
+            )
 
         # Create the omni-graph node for the randomization term
         def rep_texture_randomization():
@@ -1240,7 +1257,6 @@ def rep_texture_randomization():
                 rep.randomizer.texture(
                     textures=texture_paths, project_uvw=True, texture_rotate=rep.distribution.uniform(*texture_rotation)
                 )
-
             return prims_group.node
 
         # Register the event to the replicator

source/isaaclab/test/envs/test_texture_randomization.py

@@ -20,6 +20,7 @@
 import math
 import torch
 import unittest
+from unittest.mock import patch
 
 import omni.usd
 
@@ -127,6 +128,36 @@ class EventCfg:
     )
 
 
+@configclass
+class EventCfgFallback:
+    """Configuration for events that tests the fallback mechanism."""
+
+    # Test fallback when /visuals pattern doesn't match
+    test_fallback_texture_randomizer = EventTerm(
+        func=mdp.randomize_visual_texture_material,
+        mode="reset",
+        params={
+            "asset_cfg": SceneEntityCfg("robot", body_names=["slider"]),
+            "texture_paths": [
+                f"{NVIDIA_NUCLEUS_DIR}/Materials/Base/Wood/Bamboo_Planks/Bamboo_Planks_BaseColor.png",
+                f"{NVIDIA_NUCLEUS_DIR}/Materials/Base/Wood/Cherry/Cherry_BaseColor.png",
+            ],
+            "event_name": "test_fallback_texture_randomizer",
+            "texture_rotation": (0.0, 0.0),
+        },
+    )
+
+    reset_cart_position = EventTerm(
+        func=mdp.reset_joints_by_offset,
+        mode="reset",
+        params={
+            "asset_cfg": SceneEntityCfg("robot", joint_names=["slider_to_cart"]),
+            "position_range": (-1.0, 1.0),
+            "velocity_range": (-0.1, 0.1),
+        },
+    )
+
+
 @configclass
 class CartpoleEnvCfg(ManagerBasedEnvCfg):
     """Configuration for the cartpole environment."""
@@ -150,6 +181,29 @@ def __post_init__(self):
         self.sim.dt = 0.005  # sim step every 5ms: 200Hz
 
 
+@configclass
+class CartpoleEnvCfgFallback(ManagerBasedEnvCfg):
+    """Configuration for the cartpole environment that tests fallback mechanism."""
+
+    # Scene settings
+    scene = CartpoleSceneCfg(env_spacing=2.5)
+
+    # Basic settings
+    actions = ActionsCfg()
+    observations = ObservationsCfg()
+    events = EventCfgFallback()
+
+    def __post_init__(self):
+        """Post initialization."""
+        # viewer settings
+        self.viewer.eye = (4.5, 0.0, 6.0)
+        self.viewer.lookat = (0.0, 0.0, 2.0)
+        # step settings
+        self.decimation = 4  # env step every 4 sim steps: 200Hz / 4 = 50Hz
+        # simulation settings
+        self.sim.dt = 0.005  # sim step every 5ms: 200Hz
+
+
 class TestTextureRandomization(unittest.TestCase):
     """Test for texture randomization"""
 
@@ -186,6 +240,43 @@ def test_texture_randomization(self):
 
                 env.close()
 
+    def test_texture_randomization_fallback(self):
+        """Test texture randomization fallback mechanism when /visuals pattern doesn't match."""
+
+        def mock_find_matching_prim_paths(pattern):
+            """Mock function that simulates a case where /visuals pattern doesn't match."""
+            # If the pattern contains '/visuals', return empty list to trigger fallback
+            if pattern.endswith('/visuals'):
+                return []
+
+        for device in ["cpu", "cuda"]:
+            with self.subTest(device=device):
+                # create a new stage
+                omni.usd.get_context().new_stage()
+
+                # set the arguments - use fallback config
+                env_cfg = CartpoleEnvCfgFallback()
+                env_cfg.scene.num_envs = 16
+                env_cfg.scene.replicate_physics = False
+                env_cfg.sim.device = device
+
+                with patch.object(mdp.events.sim_utils, 'find_matching_prim_paths', side_effect=mock_find_matching_prim_paths):
+                    # This should trigger the fallback mechanism and log the fallback message
+                    env = ManagerBasedEnv(cfg=env_cfg)
+
+                    # simulate physics
+                    with torch.inference_mode():
+                        for count in range(20):  # shorter test for fallback
+                            # reset every few steps to check nothing breaks
+                            if count % 10 == 0:
+                                env.reset()
+                            # sample random actions
+                            joint_efforts = torch.randn_like(env.action_manager.action)
+                            # step the environment
+                            env.step(joint_efforts)
+
+                    env.close()
+
     def test_texture_randomization_failure_replicate_physics(self):
         """Test texture randomization failure when replicate physics is set to True."""
         # create a new stage