Zhongguan Liu

Azimuth-LIO: Robust LiDAR-Inertial Odometry via Azimuth-Aware Voxelization and Probabilistic Fusion

Voxel-based LiDAR–inertial odometry (LIO) is accurate and efficient but can suffer from geometric inconsistencies when single-Gaussian voxel models indiscriminately merge observations from conflicting viewpoints. To address this limitation, we propose Azimuth-LIO, a robust voxel-based LIO framework