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Robots delivering services to moving people: Individual vs. group patrolling strategies

机译:机器人为移动人员提供服务:个人与团队巡逻策略

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In this paper, we address the problem of serving people by a set of mobile robots. As people move we model this problem as a dynamic patrolling task, that we call the robotwaiters problem. We propose different criteria and metrics suitable to this problem, by considering not only the time to patrol all the people but also the equity of the delivery. We propose and compare four algorithms, two are based on standard solutions to the static patrolling and two are defined according the specificity of patrolling moving entities. The last one introduces a clustering heuristic to identify groups among the people, in order to limit the robots traveled distances. We present a simulator combining a pedestrian model and a robotic model. Experimental results show the efficiency of the specific new approaches. We also discuss the influence of the number of robots on the performances.
机译:在本文中,我们解决了通过一组移动机器人为人们服务的问题。随着人们的移动,我们将此问题建模为动态巡逻任务,我们将其称为robotwaiters问题。我们不仅考虑巡视所有人员的时间,而且考虑交付的公平性,提出适用于此问题的不同标准和度量标准。我们提出并比较了四种算法,两种基于静态巡逻的标准解决方案,另外两种是根据巡逻移动实体的特殊性定义的。最后一个介绍了一种聚类启发法,以识别人群中的人群,以限制机器人的行进距离。我们提出了结合行人模型和机器人模型的模拟器。实验结果表明了特定新方法的有效性。我们还将讨论机器人数量对表演的影响。

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