DFPC-SLAM:A Dynamic Feature Point Constraints-Based SLAM Using Stereo Vision for Dynamic Environment  

作　　者：Bo Zeng Chengqun Song Cheng Jun Yuhang Kang 

机构地区：[1]CAS Key Laboratory of Human-Machine Intelligence-Synergy System Shenzhen Institute of Advanced Technology Chinese Academy of Sciences Shenzhen 518055,P.R.China [2]University of Chinese Academy of Sciences Beijing,P.R.China [3]The Chinese University of Hong Kong Hong Kong,P.R.China

出　　处：《Guidance, Navigation and Control》2023年第1期46-60,共15页制导、导航与控制（英文）

基　　金：the National Natural Science Foundation of China(U21A20487);Shenzhen Technology Project(JCYJ20180507182610734)and CAS Key Technology Talent Program.

摘　　要：Visual SLAM methods usually presuppose that the scene is static, so the SLAM algorithm formobile robots in dynamic scenes often results in a signicant decrease in accuracy due to thein°uence of dynamic objects. In this paper, feature points are divided into dynamic and staticfrom semantic information and multi-view geometry information, and then static region featurepoints are added to the pose-optimization, and static scene maps are established for dynamicscenes. Finally, experiments are conducted in dynamic scenes using the KITTI dataset, and theresults show that the proposed algorithm has higher accuracy in highly dynamic scenes comparedto the visual SLAM baseline.

关 键 词：SLAM stereo vision semantic segmentation multi-view geometry dynamic scenes. 

分 类 号：TP391.41[自动化与计算机技术—计算机应用技术]