Fault-Tolerant Robot Gathering Problems on Graphs With Arbitrary Appearing Times

S. Rajsbaum, Armando Castañeda, D. Flores-Peñaloza, Manuel Alcántara
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引用次数: 8

Abstract

The LOOK-COMPUTE-MOVE model for a set of autonomous robots has been thoroughly studied for over two decades. Each robot repeatedly LOOKS at its surroundings and obtains a snapshot containing the positions of all robots; based on this information, the robot COMPUTES a destination and then MOVES to it. Previous work assumed all robots are present at the beginning of the computation. What would be the effect of robots appearing asynchronously? This paper studies thisquestion, for problems of bringing the robots close together, andexposes an intimate connection with combinatorial topology. A central problem in the mobile robots area is the gathering problem. In its discrete version, the robots start at vertices in some graph G known to them, move towards the same vertex and stop. The paper shows that if robots are asynchronous and may crash, then gathering is impossible for any graph G with at least two vertices, even if robots can have unique IDs, remember the past, know the same names for the vertices of G and use an arbitrary number of lights to communicate witheach other. Next, the paper studies two weaker variants of gathering: edge gathering and 1-gathering. For both problems we present possibility and impossibility results. The solvability of edge gathering is fully characterized: it is solvable for three or more robots on a given graph if and only if the graph is acyclic. Finally, general robot tasks in a graph are considered. A combinatorial topology characterization for the solvable tasks is presented, by a reduction of the asynchronous fault-tolerant LOOK-COMPUTE-MOVE model to a wait-free read/write shared-memory computing model, bringing together two areas that have been independently studied for a long time into a common theoretical foundation.
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容错机器人在任意出现时间图上的采集问题
一组自主机器人的LOOK-COMPUTE-MOVE模型已经被深入研究了二十多年。每个机器人反复观察周围环境,并获得包含所有机器人位置的快照;基于这些信息,机器人计算出一个目的地,然后向它移动。以前的工作假设在计算开始时所有的机器人都在场。机器人异步出现会产生什么影响?本文研究了这一问题,并揭示了其与组合拓扑的密切联系。移动机器人领域的一个核心问题是采集问题。在离散版本中,机器人从已知的某个图G的顶点开始,向同一个顶点移动并停止。本文表明,如果机器人是异步的,并且可能会崩溃,那么对于任何至少有两个顶点的图G来说,即使机器人可以有唯一的id,记住过去,知道G顶点的相同名称,并且使用任意数量的灯来相互通信,也不可能进行收集。其次,本文研究了两种较弱的聚类:边聚类和1聚类。对于这两个问题,我们都给出了可能和不可能的结果。边集的可解性是完全表征的:当且仅当图为无环时,在给定图上有三个或三个以上的机器人可解。最后,考虑了图中的一般机器人任务。通过将异步容错LOOK-COMPUTE-MOVE模型简化为无等待读写共享内存计算模型,提出了可解任务的组合拓扑表征,将两个长期独立研究的领域整合为一个共同的理论基础。
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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