MS-Mapper: A LiDAR Mapping System by Switching Between Mobile and Stationary Configurations

This article introduces the design and implementation of MS-Mapper, a LiDAR mapping system incorporating a mechanical structure based on a step motor and steering gear. The hardware configuration of MS-Mapper allows for adjustable vertical and horizontal orientations of the LiDAR sensor. The MS-Mapper has two configurations during the mapping process: stationary mapping (S-mapping), which is dedicated to generating detailed point cloud maps and providing pose drift correction, mobile mapping (M-mapping), which is utilized for completing map cavities and ensuring comprehensive coverage mapping. This dual-configuration approach employed by MS-Mapper significantly enhances pose estimation accuracy, particularly in challenging environments such as lengthy corridors. To further improve pose estimation accuracy, we propose a residual selection-based bundle adjustment (BA) algorithm. Additionally, we propose a dynamic Gaussian mixture model (GMM) tree map representation, which is designed to accommodate dynamic growth. This representation effectively reduces the number of redundant Gaussian models and minimizes data association costs compared to utilizing a dense point cloud. Furthermore, a configuration selection algorithm is proposed to detect pose estimation degeneration and determine optimal opportunities for switching configurations. In summary, the MS-Mapper system amalgamates the strengths of the traditional terrestrial laser scanner (TLS) and LiDAR simultaneous localization and mapping (SLAM) approaches. MS-Mapper provides a robust solution for achieving accurate mapping results.