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Sonar Imaging Simulation in Real-time Obstacle Avoidance algorithm for AUV Based on Creator/Vega
Gao L(高雷); Xu HL(徐红丽); Hu ZQ(胡志强)
作者部门海洋信息技术装备中心
会议名称2017 The 2nd International Conference on Robotics, Control and Automation (ICRCA 2017)
会议日期September 15-18, 2017
会议地点Kitakyushu, Japan
会议录名称2017 The 2nd International Conference on Robotics, Control and Automation (ICRCA 2017)
出版者ACM
出版地New York
2017
页码60-63
收录类别EI ; CPCI(ISTP)
EI收录号20175204569593
WOS记录号WOS:000442640500013
产权排序1
ISBN号978-1-4503-5327-4
关键词Sonar Imaging Simulation Sonar Physical Model Creator/vega
摘要

In this paper, a new approach to AUV autonomous obstacle avoidance is presented, which can be used to simulate the underwater obstacle environment, and simulates the process of AUV underwater autonomous obstacle avoidance behavior. The research is based on relevance technology and technological process of Creator modeling. The technology abroad requirement and huge application foreground in military and for civil use, because it can improve efficiency and reduce costs. The obstacle model is guided into Vega, after that, we can use the sonar simulate module to simulate imaging simulation of forwardlooking sonar system by set reasonable parameters, it can emulation really forward-looking sonar image and the obstacle information. Finally, simulation experiments show that this method is easy to computer implementation, and conform to the real obstacle avoidance based on sonar image process and display. It can be fully validated underwater autonomous obstacle avoidance algorithm.

语种英语
引用统计
文献类型会议论文
条目标识符http://ir.sia.cn/handle/173321/21296
专题海洋信息技术装备中心
通讯作者Gao L(高雷)
作者单位1.State Key Laboratory of Robotics, Shenyang Institute of Automation CAS, Shenyang, China
2.State Key Laboratory of Robotics Shenyang Institute of Automation CAS, Shenyang, China
3.State Key Laboratory of Robotics, Shenyang Institute of Automation CAS, Shenyang, China
推荐引用方式
GB/T 7714
Gao L,Xu HL,Hu ZQ. Sonar Imaging Simulation in Real-time Obstacle Avoidance algorithm for AUV Based on Creator/Vega[C]. New York:ACM,2017:60-63.
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