Test and check for texture randomization

CONTRIBUTORS.md

@@ -48,6 +48,7 @@ Guidelines for modifications:
 * Gary Lvov
 * Giulio Romualdi
 * Haoran Zhou
+* Harsh Patel
 * HoJin Jeon
 * Hongwei Xiong
 * Iretiayo Akinola

source/extensions/omni.isaac.lab/omni/isaac/lab/envs/mdp/events.py

@@ -196,6 +196,13 @@ def __init__(self, cfg: EventTermCfg, env: ManagerBasedEnv):
         event_name = cfg.params.get("event_name")
         texture_rotation = cfg.params.get("texture_rotation", (0.0, 0.0))
 
+        # check to make sure replicate_physics is set to False, else raise warning
+        if env.cfg.scene.replicate_physics:
+            raise ValueError(
+                "Unable to randomize visual texture material - ensure InteractiveSceneCfg's replicate_physics parameter"
+                " is set to False."
+            )
+
         # convert from radians to degrees
         texture_rotation = tuple(math.degrees(angle) for angle in texture_rotation)
 
@@ -212,9 +219,7 @@ def __init__(self, cfg: EventTermCfg, env: ManagerBasedEnv):
 
         # Create the omni-graph node for the randomization term
         def rep_texture_randomization():
-            prims_group = rep.get.prims(
-                path_pattern=f"{asset_entity.cfg.prim_path}/{body_names_regex}/visuals"
-            )
+            prims_group = rep.get.prims(path_pattern=f"{asset_entity.cfg.prim_path}/{body_names_regex}/visuals")
 
             with prims_group:
                 rep.randomizer.texture(

source/extensions/omni.isaac.lab/test/envs/check_texture_randomization.py

@@ -0,0 +1,203 @@
+# Copyright (c) 2022-2025, The Isaac Lab Project Developers.
+# All rights reserved.
+#
+# SPDX-License-Identifier: BSD-3-Clause
+
+"""
+This script checks the functionality of texture randomization applied to the cartpole scene.
+"""
+
+"""Launch Isaac Sim Simulator first."""
+
+
+import argparse
+
+from omni.isaac.lab.app import AppLauncher
+
+# add argparse arguments
+parser = argparse.ArgumentParser(description="Check applying texture randomization to the cartpole scene.")
+parser.add_argument("--num_envs", type=int, default=16, help="Number of environments to spawn.")
+parser.add_argument(
+    "--replicate_physics",
+    type=bool,
+    default=False,
+    help="Replicates physics properties across all environments. For texture randomization, it must be set to False.",
+)
+
+# append AppLauncher cli args
+AppLauncher.add_app_launcher_args(parser)
+# parse the arguments
+args_cli = parser.parse_args()
+
+# launch omniverse app
+app_launcher = AppLauncher(args_cli)
+simulation_app = app_launcher.app
+
+"""Rest everything follows."""
+
+import math
+import torch
+
+import omni.isaac.lab.envs.mdp as mdp
+from omni.isaac.lab.envs import ManagerBasedEnv, ManagerBasedEnvCfg
+from omni.isaac.lab.managers import EventTermCfg as EventTerm
+from omni.isaac.lab.managers import ObservationGroupCfg as ObsGroup
+from omni.isaac.lab.managers import ObservationTermCfg as ObsTerm
+from omni.isaac.lab.managers import SceneEntityCfg
+from omni.isaac.lab.utils import configclass
+from omni.isaac.lab.utils.assets import NVIDIA_NUCLEUS_DIR
+
+from omni.isaac.lab_tasks.manager_based.classic.cartpole.cartpole_env_cfg import CartpoleSceneCfg
+
+
+@configclass
+class ActionsCfg:
+    """Action specifications for the environment."""
+
+    joint_efforts = mdp.JointEffortActionCfg(asset_name="robot", joint_names=["slider_to_cart"], scale=5.0)
+
+
+@configclass
+class ObservationsCfg:
+    """Observation specifications for the environment."""
+
+    @configclass
+    class PolicyCfg(ObsGroup):
+        """Observations for policy group."""
+
+        # observation terms (order preserved)
+        joint_pos_rel = ObsTerm(func=mdp.joint_pos_rel)
+        joint_vel_rel = ObsTerm(func=mdp.joint_vel_rel)
+
+        def __post_init__(self) -> None:
+            self.enable_corruption = False
+            self.concatenate_terms = True
+
+    # observation groups
+    policy: PolicyCfg = PolicyCfg()
+
+
+@configclass
+class EventCfg:
+    """Configuration for events."""
+
+    # on reset
+    cart_texture_randomizer = EventTerm(
+        func=mdp.randomize_visual_texture_material,
+        mode="reset",
+        params={
+            "asset_cfg": SceneEntityCfg("robot", body_names=["cart"]),
+            "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",
+                f"{NVIDIA_NUCLEUS_DIR}/Materials/Base/Wood/Oak/Oak_BaseColor.png",
+                f"{NVIDIA_NUCLEUS_DIR}/Materials/Base/Wood/Timber/Timber_BaseColor.png",
+                f"{NVIDIA_NUCLEUS_DIR}/Materials/Base/Wood/Timber_Cladding/Timber_Cladding_BaseColor.png",
+                f"{NVIDIA_NUCLEUS_DIR}/Materials/Base/Wood/Walnut_Planks/Walnut_Planks_BaseColor.png",
+            ],
+            "event_name": "cart_texture_randomizer",
+            "texture_rotation": (math.pi / 2, math.pi / 2),
+        },
+    )
+
+    pole_texture_randomizer = EventTerm(
+        func=mdp.randomize_visual_texture_material,
+        mode="reset",
+        params={
+            "asset_cfg": SceneEntityCfg("robot", body_names=["pole"]),
+            "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",
+                f"{NVIDIA_NUCLEUS_DIR}/Materials/Base/Wood/Oak/Oak_BaseColor.png",
+                f"{NVIDIA_NUCLEUS_DIR}/Materials/Base/Wood/Timber/Timber_BaseColor.png",
+                f"{NVIDIA_NUCLEUS_DIR}/Materials/Base/Wood/Timber_Cladding/Timber_Cladding_BaseColor.png",
+                f"{NVIDIA_NUCLEUS_DIR}/Materials/Base/Wood/Walnut_Planks/Walnut_Planks_BaseColor.png",
+            ],
+            "event_name": "pole_texture_randomizer",
+            "texture_rotation": (math.pi / 2, math.pi / 2),
+        },
+    )
+
+    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),
+        },
+    )
+
+    reset_pole_position = EventTerm(
+        func=mdp.reset_joints_by_offset,
+        mode="reset",
+        params={
+            "asset_cfg": SceneEntityCfg("robot", joint_names=["cart_to_pole"]),
+            "position_range": (-0.125 * math.pi, 0.125 * math.pi),
+            "velocity_range": (-0.01 * math.pi, 0.01 * math.pi),
+        },
+    )
+
+
+@configclass
+class CartpoleEnvCfg(ManagerBasedEnvCfg):
+    """Configuration for the cartpole environment."""
+
+    # Scene settings
+    scene = CartpoleSceneCfg(env_spacing=2.5)
+
+    # Basic settings
+    actions = ActionsCfg()
+    observations = ObservationsCfg()
+    events = EventCfg()
+
+    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
+
+
+def main():
+    """Main function."""
+    # parse the arguments
+    env_cfg = CartpoleEnvCfg()
+    env_cfg.scene.num_envs = args_cli.num_envs
+    env_cfg.scene.replicate_physics = args_cli.replicate_physics
+
+    # setup base environment
+    env = ManagerBasedEnv(cfg=env_cfg)
+
+    # simulate physics
+    count = 0
+    while simulation_app.is_running():
+        with torch.inference_mode():
+            # reset
+            if count % 300 == 0:
+                count = 0
+                env.reset()
+                print("-" * 80)
+                print("[INFO]: Resetting environment...")
+                print("[INFO]: A new set of random textures have been applied.")
+
+            # sample random actions
+            joint_efforts = torch.randn_like(env.action_manager.action)
+            # step the environment
+            env.step(joint_efforts)
+
+            # update counter
+            count += 1
+
+    # close the environment
+    env.close()
+
+
+if __name__ == "__main__":
+    # run the main function
+    main()
+    # close sim app
+    simulation_app.close()