工矿自动化2026，Vol.52Issue(3)：15-22,8.DOI:10.13272/j.issn.1671-251x.2025120021
融合点云强度约束的煤矿井下激光SLAM算法
Laser SLAM algorithm for underground coal mines based on fusing point cloud intensity constraints
摘要
Abstract
Feature matching-based Simultaneous Localization and Mapping(SLAM)algorithms rely on sufficient geometric feature information.In challenging scenarios such as underground coal mines and long corridors,geometric features may be insufficient,which leads to mismatches in SLAM systems.To address this problem,a laser SLAM algorithm for underground coal mines based on fusing point cloud intensity constraints was proposed.On the basis of traditional geometric feature extraction,the reflectance intensity information of point clouds was fully utilized,and texture features were additionally extracted as constraints for pose estimation,thereby improving the accuracy and stability of pose estimation in scenarios with weak geometric information.A loop closure detection algorithm based on the Intensity Scan Context(ISC)descriptor was designed,which used intensity distribution features to achieve more robust scene matching,thereby improving the global consistency of pose graph optimization.The algorithm was validated through tests in narrow corridors and real underground coal mine environments.The results showed that,compared with mainstream laser SLAM algorithms,the proposed algorithm exhibited significant robustness in feature-degraded scenarios.The maximum horizontal localization error was 0.426 m and the maximum elevation error was 1.801 m.The overall localization accuracy and system robustness were significantly improved.关键词
激光SLAM/点云强度/位姿估计/纹理特征/ISC描述子/回环检测Key words
laser SLAM/point cloud intensity/pose estimation/texture features/ISC descriptor/loop closure detection分类
矿业与冶金引用本文复制引用
李小涛,贺磊,刘峰,贺永成,蔺小虎,张嘉萌..融合点云强度约束的煤矿井下激光SLAM算法[J].工矿自动化,2026,52(3):15-22,8.基金项目
国家自然科学基金青年项目(42201484) （42201484）
陕西省煤田地质集团有限公司2023年重大科技专项项目(SMDZ-2023ZD-3). （SMDZ-2023ZD-3）
