What problem does it solve? Tuning Google Cartographer for ROS 2 involves dozens of interdependent Lua parameters across local SLAM, scan matching, and the pose graph, and misconfigured values cause map tearing, drift, and false loop closures that are hard to diagnose. ## Core Features & Use Cases - Local SLAM Configuration: Set trajectory builder parameters including min/max range, submap size, grid resolution, and IMU usage for scan insertion. - Scan Matcher Tuning: Configure the real-time correlative scan matcher and Ceres refinement weights to handle featureless corridors and noisy odometry. - Pose Graph & Loop Closure Control: Adjust constraint builder scores, sampling ratios, and Huber loss to prevent false loop closures and map tearing. - Use Case: Your indoor differential-drive robot produces a torn map every time it revisits a corridor. Use this Skill to raise the loop closure min_score, tune the Huber scale, and generate a complete working .lua configuration plus ROS 2 launch integration. ## Quick Start Ask the assistant to generate a tuned Cartographer Lua configuration for an indoor differential-drive robot with a single 2D lidar and IMU.
