A prey-predator model for efficient robot tracking
Tang FZ(唐凤珍); Ji DX(冀大雄); Si BL(斯白露)
2017
会议名称2017 IEEE International Conference on Robotics and Automation, ICRA 2017
会议日期May 29 - June 3, 2017
会议地点Singapore, Singapore
页码3568-3574
通讯作者Tang FZ(唐凤珍)
中文摘要Tracking is a common topic in various areas of robotics research. Motivated by the hunting behavior of predators in nature, we propose a prey-predator model for efficient robot tracking. The head direction and speed of the pursuer is automatically adjusted according to the position and velocity of the prey. Under the situation with perception uncertainty, where the actual location of the prey is not observable, the pursuer predicts the location of the prey according to simple inference, an online adaptive autoregressive model, or an online adaptive echo state network. Simulation results demonstrate that the proposed prey-predator model is able to control the pursuer and to track the prey efficiently, even under perception uncertainty. Simple inference gives better results when the motion of the target is piecewise linear, while echo state network is more suitable when the dynamics of the target are more complex. The proposed prey-predator model thus provides an efficient method tracking targets with various statistical nature of trajectories for applications such as underwater robot tracking, human tracking and team formation.
收录类别EI
产权排序1
会议录Proceedings - IEEE International Conference on Robotics and Automation
会议录出版者IEEE
会议录出版地New York
语种英语
ISSN号1050-4729
ISBN号978-1-5090-4633-1
内容类型会议论文
源URL[http://ir.sia.cn/handle/173321/20861]  
专题沈阳自动化研究所_机器人学研究室
作者单位1.Institute of Marine Robot, Ocean College, Zhejiang University, Zhoushan, Zhejiang, 316021, China
2.State Key Laboratory of Robotics, Shenyang Institute of Automation, Chinese Academy of Sciences, Nanta Street 114, Shenyang, 110016, China
推荐引用方式
GB/T 7714
Tang FZ,Ji DX,Si BL. A prey-predator model for efficient robot tracking[C]. 见:2017 IEEE International Conference on Robotics and Automation, ICRA 2017. Singapore, Singapore. May 29 - June 3, 2017.
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