机器人2024，Vol.46Issue(4)：465-475,11.DOI:10.13973/j.cnki.robot.230131
多机协同的类脑同步定位建图方法
Multi-robot Cooperative Brain-inspired SLAM
摘要
Abstract
The advantages of low computing and storage requirements make RatSLAM,a brain-inspired navigation model,well-suitable for constructing large-scale environmental maps.To further improve the mapping efficiency,a multi-robot collaborative RatSLAM system is proposed.Firstly,a centralized multi-robot communication system is designed.Secondly,a method for detecting environment overlapped region is proposed to achieve data association between robots,so as to calculate the relative pose between experience nodes.Finally,the proposed improved graph relaxation algorithm is used to fuse the maps of multiple robots using the pose relationship between robots,to complete the real-time online construction of a globally unified experience cognitive map.The proposed method is verified on both public datasets and in a real-world physical environment to show its effectiveness.The experimental results show that,in comparison to single robot,the average mapping efficiency of multiple robots is increased by 45％,meanwhile maintaining higher map accuracy and requiring less storage.Furthermore,the proposed approach yields a much better mapping results compared with the existing map fusion methods,confirming its effectiveness and accuracy.关键词
同步定位与建图(SLAM)/类脑导航/RatSLAM/多机器人/地图融合Key words
simultaneous localization and mapping/brain-inspired navigation/RatSLAM/multi-robot/map fusion引用本文复制引用
赵杭飘,徐剑君,李涛,唐凤珍..多机协同的类脑同步定位建图方法[J].机器人,2024,46(4):465-475,11.基金项目
国家自然科学基金(62273335) （62273335）
中国科学院稳定支持基础研究领域青年团队计划(YSBR-041). （YSBR-041）
