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

Jacques Saraydaryan, F. Jumel, Olivier Simonin
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引用次数: 4

Abstract

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.
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为移动人群提供服务的机器人:个人与群体巡逻策略
在本文中,我们通过一组移动机器人来解决为人们服务的问题。当人们移动时,我们将这个问题建模为一个动态巡逻任务,我们称之为机器人服务员问题。我们提出了适合这个问题的不同标准和度量,不仅考虑了巡逻所有人的时间,而且考虑了交付的公平性。我们提出并比较了四种算法,其中两种算法是基于静态巡逻的标准解,两种算法是根据巡逻移动实体的特殊性定义的。最后一种是引入聚类启发式算法来识别人群中的群体,以限制机器人的移动距离。我们提出了一个结合行人模型和机器人模型的模拟器。实验结果表明了该方法的有效性。我们还讨论了机器人数量对性能的影响。
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