What problem does it solve? Poorly executed SLAM mapping runs produce maps with drift, phantom obstacles, and wall gaps that break robot localization and navigation. This Skill provides proven practices for planning mapping runs, configuring sensors, and cleaning up maps so the result is usable for navigation. ## Core Features & Use Cases - Mapping Run Guidance: Covers driving speed (0.2–0.3 m/s), straight-line paths, loop closure strategy, wall distance, and systematic room-by-room coverage. - Sensor Configuration Rules: Ensures lidar and IMU setups match between mapping and navigation, with checks for scan rate, range limits, and IMU calibration. - Post-Mapping Cleanup: Provides a GIMP workflow for removing exterior artifacts, fixing wall gaps, and erasing ghost obstacles, plus resolution tradeoffs and a validation checklist. - Use Case: Before mapping an office floor with a lidar-equipped robot and SLAM Toolbox, consult this Skill to plan the route, verify sensor settings, save the pose graph, and clean the PGM map before deploying it to Nav2. ## Quick Start Ask the assistant to help plan a SLAM mapping run for your robot and review the resulting map for cleanup before using it for navigation.
