Long-range navigation for autonomous robot based on topo-mapping and q-learning
Hu YM(胡艳明)1,2,5; Li DC(李德才)1,5; He YQ(何玉庆)1,3,5; Han JD(韩建达)1,4,5
2019
会议日期August 4-9, 2019
会议地点Irkutsk, Russia
页码426-431
英文摘要Long-range navigation in unknown environments is one of the major challenges for autonomous robot. Traditional methods are usually relying on metric mapping and path planning, which own a very high calculation cost for planning, re-planning, map building and map updating. Q-learning can learn a reactive navigation behavior for mobile robot, but easy fall into local minimum with long-range goal. In order to accomplish the long-range navigation task, a two-layers navigation framework is based a novel topological mapping (topo-mapping) method and Q-learning. The proposed topo-mapping method can incrementally build a topological map (topo-map) in unknown environment. Topo-map maintains two types of nodes: station node and feature node. Station nodes store low resolution information of environment and its related feature nodes store the export information. Local target can be selected from those feature nodes by proposed topology planner. This local target guides Q-learning based robot reach long-range goal. We evaluate the proposed method in simulation environment. Experimental results show that the proposed method based autonomous robot can reach the long-range goal successfully in unknown environment.
源文献作者CAS Key Laboratory of Health Informatics, Shenzhen Institutes of Advanced Technology ; CAS Key Laboratory of Human-Machine Intelligence-Synergy Systems, Shenzhen Institutes of Advanced Technology (HMISS) ; IEEE Robotics and Automation Society (RA) ; Institute of Electrical and Electronics Engineers (IEEE)
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会议录2019 IEEE International Conference on Real-Time Computing and Robotics, RCAR 2019
会议录出版者IEEE
会议录出版地New York
语种英语
ISBN号978-1-7281-3726-1
内容类型会议论文
源URL[http://ir.sia.cn/handle/173321/27175]  
专题沈阳自动化研究所_机器人学研究室
通讯作者He YQ(何玉庆)
作者单位1.Institutes for Robotics and Intelligent Manufacturing, Chinese Academy of Sciences, Shenyang, Liaoning Province 110016, China
2.University of Chinese Academy of Sciences, Beijing 100049, China
3.Shenyang Institute of Automation (Guangzhou), Chinese Academy of Sciences, Guangzhou 511458, China
4.College of Artificial Intelligence, Nankai University, Tianjing 300071, China
5.State Key Laboratory of Robotics, Shenyang Institute of Automation, Chinese Academy of Sciences, Shenyang, Liaoning Province 110016, China
推荐引用方式
GB/T 7714
Hu YM,Li DC,He YQ,et al. Long-range navigation for autonomous robot based on topo-mapping and q-learning[C]. 见:. Irkutsk, Russia. August 4-9, 2019.
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