Active Vehicle Re-localization Based on Non-repetitive LiDAR with Gimbal Motion Strategy

The installation of a multi-layer 3D LiDAR atop the vehicle is a widely adopted hardware configuration for map-matching-based localization in intelligent driving. By offering a comprehensive 360° horizontal Field of View (FoV), this setup aims to achieve precise matching outcomes through the imposition of substantial geometric constraints against dynamic interferences and structural degradation. However, several factors limit its environmental adaptability, such as sparse point cloud density at distances, insufficient maximum sensing range, and notably, the restricted beam elevation angle, limiting the perception of the environment beyond obstacles. The rapid advancement of non-repetitive scanning LiDARs shows promise in mitigating such limitations. Nevertheless, their narrow FoV remains a challenge to overcome. In this study, we propose a solution by mounting such one single LiDAR on a two-axis rotating gimbal, enabling the vehicle to surpass the ranges and vertical FoV limitations of traditional setups actively. The corresponding gimbal motion strategy has been designed to automatically focus on the environment component with the most robust geometric constraints. Experimental results validate that the proposed method achieves superior robustness under high dynamic interference while delivering sufficient performance under standard conditions.