A LiDAR Mapping System for Robot Navigation in Dynamic Environments

作者：Zhiguo Zhou, Xin Feng, Shunfan Di, Xuehua Zhou · 发表于：IEEE Transactions on Intelligent Vehicles · 年份：2023 · DOI：10.1109/tiv.2023.3328013 · 被引用次数：24 · 研究领域：Robotics and Sensor-Based Localization、Robotic Path Planning Algorithms、Advanced Image and Video Retrieval Techniques

Simultaneous Localization and Mapping (SLAM) technology based on multi-line LiDAR enables real-time robot positioning and environment mapping in unknown environments. However, three-dimensional point cloud maps constructed in this way cannot be used directly for navigation. Meanwhile, during the mapping of complex dynamic scenes, the interference of dynamic objects will result in maps with artifacts, which exist in the form of obstacles in the map, causing adverse effects on the subsequent navigation. To solve these problems, we propose a LiDAR mapping system suitable for robot navigation in dynamic environment. Firstly, a LiDAR SLAM algorithm based on intensity scanning context (ISC) loop closure detection is proposed to construct the original 3D point cloud image, it can effectively suppress the pose drift of odometer, and ensure the real-time performance of the algorithm with the addition of loop closure detection module. Then we design a method to obtain a two-dimensional grid map suitable for robot navigation, after filtering false obstacles caused by dynamic object trajectories in the original point cloud map, a composite filter is used to further filter the point cloud map to avoid the influence of uneven ground point cloud on navigation, then a two-dimensional grid map is obtained through probabilistic updating. The experimental results show that the mapping system is suitable for global navigation, and the positioning accuracy of the proposed algorithm on KITTI data ...