Path planning for swarm AUV visiting communication node

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	Path planning for swarm AUV visiting communication node
	Geng C(耿超)2,3,4; Li GN(李冠男)1,2,3; Xu HL(徐红丽)2,3
	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
内容类型	会议论文
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.University of Chinese Academy of Sciences, Beijing 100049, China 2.(Institutes for Robotics and Intelligent Manufacturing, China Academy of Science (CAS), Shenyang 110016, China 3.The State Key Laboratory of Robotics, Shenyang Institute of Automation, China Academy of Science (CAS), Shenyang 110016, China 4.School of Information Science and Engineering, Northeastern University, Shenyang 110819, 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.