GenZ-LIO: Generalizable LiDAR-Inertial Odometry Beyond Confined--Open Boundaries
GenZ-LIO is a generalizable LiDAR-inertial odometry framework designed to handle localization in environments with varying spatial scales, such as moving between confined and open areas. It achieves this by using scale-aware voxelization to adjust scan density, a hybrid Kalman filter for more reliable state updates, and a pruned search method for faster matching. This results in robust odometry that maintains stability across diverse field conditions.