lidar-odometry

You can estimate robot motion by configuring backends like rf2o_laser_odometry or kiss-icp to match consecutive scans. This Skill outputs nav_msgs/Odometry data designed to fuse with EKF or SLAM pipelines in ROS 2.

Lidar odometry is used instead of wheel odometry to enhance localization in low-slip or feature-rich environments. It provides robust ego-motion estimates using scan matching when wheel-based estimates are unreliable or biased.

Yes, you can generate 3D point cloud odometry using the kiss-icp backend. The Skill supports cross-backend compatibility, allowing you to configure kiss-icp alongside 2D options like rf2o_laser_odometry and scan_tools.

The best way to fuse lidar odometry with an EKF pipeline is to output nav_msgs/Odometry from your configured scan matching backend and integrate it directly. The Skill is specifically designed for integration with EKF-based localization workflows.

Yes, ROS 2 lidar odometry supports both 2D laser scans and 3D point clouds. It utilizes backends like rf2o_laser_odometry and scan_tools for 2D scenarios, and kiss-icp for 3D ego-motion estimation.

You should not use scan matching for ego-motion estimation in environments lacking geometric features or with extreme dynamic obstacles, as lidar odometry relies on matching consecutive point clouds to produce reliable nav_msgs/Odometry.