obstacle-layer

To handle multiple sensors in a Nav2 costmap, configure independent observation sources like scan and depth_camera. The obstacle layer processes each source separately for marking and clearing to maintain accurate obstacle detection.

Phantom obstacles in a Nav2 costmap appear when stale data is not cleared properly. Using raytrace clearing along sensor rays and configuring expected_update_rate checks ensures old obstacle cells are removed as the robot moves.

To clear lethal obstacles under the robot footprint in ROS2, enable footprint_clearing_enabled in your obstacle layer. This clears cells directly beneath the robot to prevent the costmap from treating the robot's own body as an obstacle.

Yes, you can configure obstacle_range and raytrace_range per sensor in Nav2. The obstacle layer satisfies per-source configuration requirements, allowing independent marking and clearing toggles for multiple observation sources.

To detect stale sensor data in a ROS2 costmap obstacle layer, set the expected_update_rate parameter. This real-time validation feature monitors update rates to identify when observation sources stop providing fresh data.