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Research on AUV Obstacle Avoidance Based on BP Neural Network
Dong LY(董凌艳); Xu HL(徐红丽)
Department海洋信息技术装备中心
Conference Name2017 The 2nd International Conference on Robotics, Control and Automation (ICRCA 2017)
Conference DateSeptember 15-18, 2017
Conference PlaceKitakyushu, Japan
Source Publication2017 The 2nd International Conference on Robotics, Control and Automation (ICRCA 2017)
PublisherACM
Publication PlaceNew York
2017
Pages26-29
Indexed ByEI ; CPCI(ISTP)
EI Accession number20175204569586
WOS IDWOS:000442640500006
Contribution Rank1
ISBN978-1-4503-5327-4
KeywordObstacle Avoidance Auv Bp Neural Network.
Abstract

Autonomous underwater vehicle should have real-time obstacle avoidance ability of self-protection in autonomous operation in unknown environment. A three-dimensional real-time obstacle avoidance method is proposed for under-actuated AUV with the distance sensor as obstacle avoidance sensor. The output information of the distance sensor is converted into a dangerous degree which as the input of BP neural network. The output of BP neural network is the heading or the depth of AUV which is to be adjusted. The effectiveness of obstacle avoidance method based on BP neural network is verified by MATLAB simulation.

Language英语
Citation statistics
Document Type会议论文
Identifierhttp://ir.sia.cn/handle/173321/21295
Collection海洋信息技术装备中心
Corresponding AuthorDong LY(董凌艳)
Affiliation1.State Key Laboratory of Robotics, Shenyang Institute of Automation, Chinese Academy of Science, Shenyang, China
2.University of Chinese Academy of Science, Beijing, China
3.State Key Laboratory of Robotics, Shenyang Institute of Automation, Chinese Academy of Science, Shenyang, China
Recommended Citation
GB/T 7714
Dong LY,Xu HL. Research on AUV Obstacle Avoidance Based on BP Neural Network[C]. New York:ACM,2017:26-29.
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