Maximizing the throughput of a patrolling UAV by dynamic programming

K. Krishnamoorthy, M. Pachter, P. Chandler
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引用次数: 3

Abstract

This paper addresses the following base defense scenario: an Unmanned Aerial Vehicle (UAV) performs the task of perimeter alert patrol. There are m alert stations/sites located on the perimeter where a nearby breaching of the perimeter by an intruder can be sensed and is flagged by an Unattended Ground Sensor (UGS). We assume that the alert arrival process is Poisson. In order to determine whether an incursion flagged by a UGS is a false alarm or a real threat, a patrolling UAV flies to the alert site to investigate the alert. The decision problem for a UAV is to determine, in real-time, which station to head toward next, upon completion of a service, so as to maximize the system throughput or equivalently minimize the mean waiting time of an alert in the system. The throughput is defined as the number of messages/alerts serviced on average in unit time.
基于动态规划的巡逻无人机吞吐量最大化问题
本文研究了以下基地防御场景:一架无人机(UAV)执行周边警戒巡逻任务。在外围设有m个警报站/地点,当附近有入侵者突破外围时,警报站/地点可被感应到,并由无人值守地面传感器(UGS)标记。我们假设警报到达过程是泊松过程。为了确定由UGS标记的入侵是假警报还是真正的威胁,一架巡逻无人机飞到警报地点调查警报。无人机的决策问题是在完成一项服务后,实时确定下一站的飞行方向,使系统吞吐量最大化,或者说使系统中警报的平均等待时间最小化。吞吐量定义为单位时间内平均处理的消息/警报数量。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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