机器人2024，Vol.46Issue(4)：436-449,14.DOI:10.13973/j.cnki.robot.230244
考虑点云结构和表观信息的激光雷达-惯性SLAM算法
LiDAR-inertial SLAM Algorithm Based on Point Cloud Structure and Appearance
摘要
Abstract
To enhance precise navigation capabilities of mobile robots operating in the satellite-denied environments and to mitigate accumulated positioning error in the large-scope motion scenarios,a LiDAR(light detection and ranging)-inertial SLAM(simultaneous localization and mapping)algorithm based on point cloud structure and appearance is proposed.The proposed algorithm consists of two parts:the LiDAR-inertial odometry considering the point cloud structure,and the loop closure detection and optimization based on the point cloud appearance.In the part of LiDAR-inertial odometry,navigation states are predicted by IMU(inertial measurement unit)information,a direct alignment observation equation is constructed with the point cloud structure considered,and navigation states are updated in real-time by an iterative error extended Kalman filter.In the part of loop closure detection and optimization,keyframes are identified by evaluating discrepancies in point cloud appearance,relative motion poses and time constraints.Then,candidate loop keyframes are screened out based on point cloud appearances.The candidate loop keyframes are subsequently sorted according to the appearance matching distances and the two-dimensional distances.Finally,the loop keyframe is confirmed and the pose graph is constructed for the global pose optimization and the map adjustment.Autonomous navigation experiments in Xi'an Expo Park show that autonomous navigation is realized in real-time,the loops are accurately detected in the loop motion,and the loop optimization is effectively completed by the proposed algorithm.The average error between the starting and ending points of trajectories is only 0.07 m.Moreover,a multimodal integrated navigation switching method in the LiDAR degradation environments is further discussed,which effectively improves the reliability of autonomous navigation.关键词
同时定位与地图创建/3维激光雷达/惯性测量单元/结构和表观/闭环检测Key words
simultaneous localization and mapping(SLAM)/3D LiDAR/inertial measurement unit(IMU)/structure and appearance/loop closure detection引用本文复制引用
姚二亮,宋海涛,赵婧,范晓婧..考虑点云结构和表观信息的激光雷达-惯性SLAM算法[J].机器人,2024,46(4):436-449,14.基金项目
中国博士后科学基金(2020M683737). （2020M683737）
