有记忆的胖机器人的模式形成

IF 0.4 4区 计算机科学 Q4 MATHEMATICS
Rusul J. Alsaedi, Joachim Gudmundsson, André van Renssen
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引用次数: 0

摘要

给定一组n≥1个自主的、匿名的、不可区分的、沉默的、可能迷失方向的移动单元磁盘(即脂肪)机器人在欧几里德平面上按照look - comput - move循环操作,我们考虑模式形成问题:从任意起始位置,机器人必须重新定位自己以形成给定的目标模式。这个问题出现在能见度受阻的情况下,如果在两个机器人之间的直线段上有第三个机器人,机器人就看不到另一个机器人。我们假设一个机器人的运动不会被对手打断,并且机器人有一个小的0(1)大小的内存,它们可以用来存储信息,但这些信息不能传递给其他机器人。为了解决这个问题,我们提出了一个分三步工作的算法。首先建立相互可见性,然后选择一个机器人作为领导者,最后形成所需的模式。整个算法运行周期为O(n)+O(qlog (n))轮,概率至少为1−n−q。该算法是无碰撞的,不需要了解机器人的数量。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Pattern formation for fat robots with memory
Given a set of n1 autonomous, anonymous, indistinguishable, silent, and possibly disoriented mobile unit disk (i.e., fat) robots operating following Look-Compute-Move cycles in the Euclidean plane, we consider the Pattern Formation problem: from arbitrary starting positions, the robots must reposition themselves to form a given target pattern. This problem arises under obstructed visibility, where a robot cannot see another robot if there is a third robot on the straight line segment between the two robots. We assume that a robot's movement cannot be interrupted by an adversary and that robots have a small O(1)-sized memory that they can use to store information, but that cannot be communicated to the other robots. To solve this problem, we present an algorithm that works in three steps. First it establishes mutual visibility, then it elects one robot to be the leader, and finally it forms the required pattern. The whole algorithm runs in O(n)+O(qlogn) rounds with probability at least 1nq. The algorithms are collision-free and do not require the knowledge of the number of robots.
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来源期刊
CiteScore
1.60
自引率
16.70%
发文量
43
审稿时长
>12 weeks
期刊介绍: Computational Geometry is a forum for research in theoretical and applied aspects of computational geometry. The journal publishes fundamental research in all areas of the subject, as well as disseminating information on the applications, techniques, and use of computational geometry. Computational Geometry publishes articles on the design and analysis of geometric algorithms. All aspects of computational geometry are covered, including the numerical, graph theoretical and combinatorial aspects. Also welcomed are computational geometry solutions to fundamental problems arising in computer graphics, pattern recognition, robotics, image processing, CAD-CAM, VLSI design and geographical information systems. Computational Geometry features a special section containing open problems and concise reports on implementations of computational geometry tools.
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