LiDAR-Inertial- Visual Fusion SLAM in Dynamic Environments

In this paper, we propose a LiDAR-Inertial-Visual multi-sensor fusion SLAM system for dynamic environments. While many state of the art multi-sensor fusion SLAM systems can achieve excellent performance in static environment, achieving high accuracy and robustness in dynamic environment remains a significant challenge. In order to address the dynamic object elimination issue during mapping, a dynamic voxel judgment method based on octree map is proposed. Spe-cifically, we perform template matching between the current frame and submap to calculate the dynamic voxel occupancy rate of point clouds in Box, so as to effectively detect dynamic objects in the environment. At the same time, we continue to track dynamic objects and eliminate them in the map. Exten-sive experiments have been conducted on the KITTI dataset and our own dataset. Results shows the proposed method can effectively eliminate dynamic objects and improve the SLAM accuracy in dynamic environments.