Probabilistic Search and Track with Multiple Mobile Agents

Savvas Papaioannou, P. Kolios, T. Theocharides, C. Panayiotou, M. Polycarpou
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引用次数: 12

Abstract

In this paper we are interested in the task of searching and tracking multiple moving targets in a bounded surveillance area with a group of autonomous mobile agents. More specifically, we assume that targets can appear and disappear at random times inside the surveillance region and their positions are random and unknown. The agents have a limited sensing range, and due to sensor imperfections they receive noisy measurements from the targets. In this work we utilize the theory of random finite sets (RFS) to capture the uncertainty in the time-varying number of targets and their states and we propose a decision and control framework, in which the mode of operation (i.e. search or track) as well as the mobility control action for each agent, at each time instance, are determined so that the collective goal of searching and tracking is achieved. Extensive simulation results demonstrate the effectiveness and performance of the proposed solution.
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多移动代理的概率搜索与跟踪
在本文中,我们感兴趣的任务是用一组自主移动代理搜索和跟踪有界监视区域内的多个运动目标。更具体地说,我们假设目标可以在监视区域内随机出现和消失,并且其位置是随机和未知的。智能体具有有限的感知范围,并且由于传感器的缺陷,它们接收来自目标的噪声测量。在这项工作中,我们利用随机有限集(RFS)理论来捕捉时变目标数量及其状态中的不确定性,并提出了一个决策和控制框架,在该框架中,每个代理在每个时间实例中确定操作模式(即搜索或跟踪)以及移动控制动作,从而实现搜索和跟踪的集体目标。大量的仿真结果证明了该方案的有效性和性能。
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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