Distributed pursuit-evasion without mapping or global localization via local frontiers
Distributed pursuit-evasion without mapping or global localization via local frontiers
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DOI：
10.1007/s10514-011-9260-1
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发表时间：
2012-01-01
影响因子：
3.5
通讯作者：
Bullo, Francesco
中科院分区：
文献类型：
--
作者：
Durham, Joseph W.;Franchi, Antonio;Bullo, Francesco
本文解决了一个基于可见性的追击躲避问题，其中一组具有有限传感和通信能力的移动机器人必须进行协调，以检测未知的多重连接平面环境中的任何躲避者。我们保证逃逸者检测的分布式算法是围绕保持已清除区域和污染区域之间边界的完全覆盖，同时扩大已清除区域而构建的。我们详细介绍了一种新颖的分布式方法，用于存储和更新该边界，而无需构建环境地图或需要全局本地化。我们通过现实环境中的模拟和硬件实验来演示该算法的功能。我们还将我们算法的蒙特卡罗结果与作为可用机器人数量函数的理论最佳清理区域进行比较。
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.