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Distributed pursuit-evasion without mapping or global localization via local frontiers

机译:分布式逃避,无需通过本地边界进行地图或全局本地化

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摘要

This paper addresses a visibility-based pursuit-evasion problem in which a team of mobile robots with limited sensing and communication capabilities must coordinate to detect any evaders in an unknown, multiply-connected planar environment. Our distributed algorithm to guarantee evader detection is built around maintaining complete coverage of the frontier between cleared and contaminated regions while expanding the cleared region. We detail a novel distributed method for storing and updating this frontier without building a map of the environment or requiring global localization. We demonstrate the functionality of the algorithm through simulations in realistic environments and through hardware experiments. We also compare Monte Carlo results for our algorithm to the theoretical optimum area cleared as a function of the number of robots available.
机译:本文解决了基于可见性的追逃问题,在该问题中,具有有限的感测和通信能力的移动机器人团队必须进行协调,以检测未知,多重连接的平面环境中的任何逃避者。我们的分布式算法可确保逃避者的检测是建立在扩大清除区域的同时,完全覆盖清除区域和受污染区域之间的边界。我们详细介绍了一种新颖的分布式方法,用于存储和更新此领域,而无需构建环境图或需要全局本地化。我们通过在现实环境中进行仿真并通过硬件实验来演示算法的功能。我们还将算法的蒙特卡洛结果与清除的理论最佳面积进行比较,该面积是可用机器人数量的函数。

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