文章基本信息

标题：AUTONOMOUS MULTI-TARGET INTERCEPTION IN DYNAMIC SETTINGS â€“ ON-LINE PURSUER TASK ALLOCATION
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作者：Patricia Kristine Sheridan ; Pawel Kosicki ; Goldie Nejat 等
期刊名称：International Journal on Smart Sensing and Intelligent Systems
印刷版ISSN：1178-5608
出版年度：2013
卷号：6
期号：4
页码：1783-1807
出版社：Massey University
摘要：In this paper, we present a generic task-allocation methodology for time-optimal, autonomous on-line interception of multiple dynamic targets by a team of robotic pursuers. The proposed novel methodology is applicable to problems consisting of numerous variations of multiple pursuers and targets. The targets are assumed to be highly maneuverable with a priori unknown, though real-time trackable, motion trajectories. Guidance theory is employed to allow each of the pursuers to navigate autonomously towards its allocated target. Numerous simulations and experiments have verified that the proposed methodology is tangibly efficient in dynamic (one-to-one) re-pairing of pursuers to targets for minimum total overall interception time.
关键词：on-line task allocation; autonomous agents; distributed systems; robot motion planning.