Manage lethal obstacle marking and clearing in a Nav2 costmap.
npx skills add https://github.com/wimblerobotics/ros2-copilot-skills --skill obstacle-layer
Please help me install this Agent Skill. Skill: obstacle-layer Source: https://github.com/wimblerobotics/ros2-copilot-skills/tree/main/obstacle-layer Command: npx skills add https://github.com/wimblerobotics/ros2-copilot-skills --skill obstacle-layer
Mark lethal obstacles in a 2D Nav2 costmap and clear them as the robot moves, using data from multiple sensors to maintain an accurate representation of the environment.
Run the obstacle-layer with your Nav2 configuration to begin marking obstacles from sensors and clearing cells during robot motion.
High-intent search queries and answers about installing and using this skill.
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.
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