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题名: Artificial potential guided evolutionary path plan for multi-vehicle multi-target pursuit
作者: Zu D(祖迪) ; Han JD(韩建达) ; Campbell, M
作者部门: 机器人学研究室
会议名称: IEEE International Conference on Robotics and Biomimetics (ROBIO 2004)
会议日期: August 22-26, 2004
会议地点: Shenyang, China
会议主办者: IEEE Robot & Automat Soc, IEEE HK RA CS Joint Chapter, Chinese Acad Sci, Shenyang Inst Automat, Chinese High tech Dev Program, Robot Soc Japan, Japan Soc Mech Engineers, Int Rescue Syst Inst, Shenyang Hunnan New Urban Area, Shenyang New & High tech Ind Dev Zone
会议录: IEEE ROBIO 2004: Proceedings of the IEEE International Conference on Robotics and Biomimetics
会议录出版者: IEEE
会议录出版地: NEW YORK
出版日期: 2004
页码: 855-861
收录类别: CPCI(ISTP) ; EI
ISBN号: 0-7803-8641-8
关键词: path plan ; multi-vehicle ; multi-target ; pursuit
摘要: Path planning for multi-vehicle multi-target pursuit (MVMTP) is studied in this paper. With respect to equal number of vehicles and obstacles, a global cost function (GCF) is proposed and an optimal one-vehicle-one-target-pair appointment is specified based on the GCF. The artificial potential (AP)-guided evolutionary algorithm (EA) is used by each appointed pair to search the path that will allow the vehicle to catch the target at a specified criterion while avoiding obstacles. Both the targets and obstacles are moving in the environment, and the pair appointment can be updated regularly according to the snapshot of the uncertain environment. The integration of AP into EA is intended to achieve a convergent, fast and efficient trajectory searching mechanism that can be installed in real time.
语种: 英语
产权排序: 1
内容类型: 会议论文
URI标识: http://ir.sia.cn/handle/173321/8590
Appears in Collections:机器人学研究室_会议论文

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Recommended Citation:
祖迪; 韩建达; Campbell, M.Artificial potential guided evolutionary path plan for multi-vehicle multi-target pursuit.见:IEEE .IEEE ROBIO 2004: Proceedings of the IEEE International Conference on Robotics and Biomimetics,NEW YORK,2004,855-861
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