Isaaclab camera path

[ahn.paf]

Problem loading camera and setting prim path

Isaac Sim Version

4.5.0

IsaacLab Version

2.1.0

Operating System

Ubuntu 22.04

Topic Description

Detailed Description

I have tried to spawn the prim path for cameracfg, but I constantly encounter a prim path error.

NV_REGEX_NS}/Leatherback/Rigid_Bodies/Chassis/Camera_Right' is not global. It must start with '

Error Messages

source/isaaclab_tasks/isaaclab_tasks/direct/leatherback/leatherback_env.py", line 104, in _setup_scene
    self.camera = Camera(cfg=self.cfg.camera_cfg)
  File "saacLab/source/isaaclab/isaaclab/sensors/camera/camera.py", line 133, in __init__
    self.cfg.spawn.func(
  File "IsaacLab/source/isaaclab/isaaclab/sim/utils.py", line 229, in wrapper
    raise ValueError(f"Prim path '{prim_path}' is not global. It must start with '/'.")
ValueError: Prim path '{ENV_REGEX_NS}/Leatherback/Rigid_Bodies/Chassis/Camera_Right' is not global. It must start with '/'.

Set the environment variable HYDRA_FULL_ERROR=1 for a complete stack trace.

Additional Information

What I’ve Tried

I have tried different camera configurations in cameracfg, I am using leatherback example for Isaaclab:

@configclass
class LeatherbackEnvCfg(DirectRLEnvCfg):
    decimation = 4
    episode_length_s = 20.0
    action_space = 2
    observation_space = 8
    state_space = 0
    sim: SimulationCfg = SimulationCfg(dt=1 / 60, render_interval=decimation)
    robot_cfg: ArticulationCfg = LEATHERBACK_CFG.replace(prim_path="/World/envs/env_.*/Robot")
    waypoint_cfg = WAYPOINT_CFG

    throttle_dof_name = [
        "Wheel__Knuckle__Front_Left",
        "Wheel__Knuckle__Front_Right",
        "Wheel__Upright__Rear_Right",
        "Wheel__Upright__Rear_Left"
    ]
    steering_dof_name = [
        "Knuckle__Upright__Front_Right",
        "Knuckle__Upright__Front_Left",
    ]

    camera_cfg: CameraCfg = CameraCfg(
        prim_path="{ENV_REGEX_NS}/Leatherback/Rigid_Bodies/Chassis/Camera_Right",
        update_period=0.1,
        width=640,
        height=480,
        data_types=["rgb", "distance_to_image_plane"],
        spawn=sim_utils.PinholeCameraCfg(
            focal_length=24.0,
            focus_distance=400.0,
            horizontal_aperture=20.955,
            clipping_range=(0.1, 1e5),
        ),
    )

and then set up the scene:

class LeatherbackEnv(DirectRLEnv):
    cfg: LeatherbackEnvCfg

    def __init__(self, cfg: LeatherbackEnvCfg, render_mode: str | None = None, **kwargs):
        super().__init__(cfg, render_mode, **kwargs)
        self._throttle_dof_idx, _ = self.leatherback.find_joints(self.cfg.throttle_dof_name)
        self._steering_dof_idx, _ = self.leatherback.find_joints(self.cfg.steering_dof_name)
        self._throttle_state = torch.zeros((self.num_envs,4), device=self.device, dtype=torch.float32)
        self._steering_state = torch.zeros((self.num_envs,2), device=self.device, dtype=torch.float32)
        self._goal_reached = torch.zeros((self.num_envs), device=self.device, dtype=torch.int32)
        self.task_completed = torch.zeros((self.num_envs), device=self.device, dtype=torch.bool)
        self._num_goals = 10
        self._target_positions = torch.zeros((self.num_envs, self._num_goals, 2), device=self.device, dtype=torch.float32)
        self._markers_pos = torch.zeros((self.num_envs, self._num_goals, 3), device=self.device, dtype=torch.float32)
        self.env_spacing = self.cfg.env_spacing
        self.course_length_coefficient = 2.5
        self.course_width_coefficient = 2.0
        self.position_tolerance = 0.15
        self.goal_reached_bonus = 10.0
        self.position_progress_weight = 1.0
        self.heading_coefficient = 0.25
        self.heading_progress_weight = 0.05
        self._target_index = torch.zeros((self.num_envs), device=self.device, dtype=torch.int32)

    def _setup_scene(self):
        # Create a large ground plane without grid
        spawn_ground_plane(
            prim_path="/World/ground",
            cfg=GroundPlaneCfg(
                size=(500.0, 500.0),  # Much larger ground plane (500m x 500m)
                color=(0.2, 0.2, 0.2),  # Dark gray color
                physics_material=sim_utils.RigidBodyMaterialCfg(
                    friction_combine_mode="multiply",
                    restitution_combine_mode="multiply",
                    static_friction=1.0,
                    dynamic_friction=1.0,
                    restitution=0.0,
                ),
            ),
        )
        self.cfg.camera_cfg.prim_path = self.cfg.camera_cfg.prim_path.format(ENV_REGEX_NS=self.scene.env_regex_ns)
        print(self.cfg.camera_cfg.prim_path)

        # Add camera
        # Instantiate the camera
        self.camera = Camera(cfg=self.cfg.camera_cfg)
        # Add camera to the scene
        self.scene.sensors["camera"] = self.camera

        # Setup rest of the scene
        self.leatherback = Articulation(self.cfg.robot_cfg)
        self.waypoints = VisualizationMarkers(self.cfg.waypoint_cfg)
        self.object_state = []
        
        self.scene.clone_environments(copy_from_source=False)
        self.scene.filter_collisions(global_prim_paths=[])
        self.scene.articulations["leatherback"] = self.leatherback

        # Add lighting
        light_cfg = sim_utils.DomeLightCfg(intensity=2000.0, color=(0.75, 0.75, 0.75))
        light_cfg.func("/World/Light", light_cfg)

[Simplychenable]

@ahn.paf i would suggest submitting your questions and inquiries via the GitHub repo following the instructions provided on Isaac Lab’s Contributing Guidelines regarding discussions, submitting issues, feature requests, and contributing to the project.

the collaborators should be able to address IsaacLab questions/bugs more efficiently.