中国科学院机构知识库网格
Chinese Academy of Sciences Institutional Repositories Grid
Path planning for swarm AUV visiting communication node

文献类型:会议论文

作者Geng C(耿超)1,2,3; Li GN(李冠男)1,2,4; Xu HL(徐红丽)1,2
出版日期2019
会议日期August 8-11, 2019
会议地点Shenyang, China
关键词Path planning AUV swarm Biological inspired neural network
页码233-239
英文摘要This paper proposes a method for path planning of an underwater robot swarm. The method is based on biological inspired neural network to plan path between robots and communication nodes. The robot swarm is used to search wild sea area. To solve the long distance communication problem, we deploy some communication nodes ahead, forming a communication network under the water. The robots visit the nodes to communicate. With this method, robots can also avoid obstacles in real time. Firstly, put the landscape into grid map. Then build biologically inspired neural network based on the grid map. The node attracts the robots and the obstacles reject the robots through neural activity. At last, robots plan their path by the activity with a steepest gradient descent rule. Simulation result shows the method may lose in local optimum, so we improve the method to avoid repetitive path. The results show that the improvement effective for path planning.
产权排序1
会议录Intelligent Robotics and Applications - 12th International Conference, ICIRA 2019, Proceedings
会议录出版者Springer Verlag
会议录出版地Berlin
语种英语
ISSN号0302-9743
ISBN号978-3-030-27534-1
WOS记录号WOS:000569253000022
源URL[http://ir.sia.cn/handle/173321/25498]  
专题沈阳自动化研究所_海洋信息技术装备中心
通讯作者Geng C(耿超)
作者单位1.The State Key Laboratory of Robotics, Shenyang Institute of Automation, China Academy of Science (CAS), Shenyang 110016, China
2.(Institutes for Robotics and Intelligent Manufacturing, China Academy of Science (CAS), Shenyang 110016, China
3.School of Information Science and Engineering, Northeastern University, Shenyang 110819, China
4.University of Chinese Academy of Sciences, Beijing 100049, China
推荐引用方式
GB/T 7714
Geng C,Li GN,Xu HL. Path planning for swarm AUV visiting communication node[C]. 见:. Shenyang, China. August 8-11, 2019.

入库方式: OAI收割

来源:沈阳自动化研究所

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