信息与控制2024，Vol.53Issue(5)：594-602,9.DOI:10.13976/j.cnki.xk.2023.0299
融合多元信息的激光SLAM回环检测方法
Laser SLAM Loop Detection Method with Multivariate Information
摘要
Abstract
In simultaneous localization and mapping(SLAM),loop detection is an important and chal-lenging problem.Existing point cloud-based loop detection usually only uses height information to construct local or global descriptors,but its single description ability leads to many false loop de-tections.In order to solve this problem,combining the height,intensity and density information,an improved global descriptor is proposed.In order to use this global descriptor for efficient loop detection,several loop candidate is searched through K-Dimensional Tree(KD-Tree)firstly,and then the idea of Hamming distance is used to calculate the distance between two frame point clouds corresponding to the global descriptor.Finally,determine the frame with the highest similarity as the loop frame.The experiment uses public data sets to test the performance of the algorithm.The results show that,compared with the comparison algorithm,the algorithm has the higher precision and recall rate.At the same time,the SLAM framework integration experiment is carried out to ob-tain superior positioning and mapping accuracy.关键词
同步定位与地图构建/激光雷达/回环检测/汉明距离/全局描述符Key words
simultaneous localization and mapping(SLAM)/LiDAR/loop detection/Hamming distance/global descriptor分类
信息技术与安全科学引用本文复制引用
虞沈豪,魏国亮,张顺,刘铭..融合多元信息的激光SLAM回环检测方法[J].信息与控制,2024,53(5):594-602,9.基金项目
国家自然科学基金(62273239) （62273239）
