测地线相互可见性问题:网格和树木上的遗忘机器人

IF 3 3区 计算机科学 Q2 COMPUTER SCIENCE, INFORMATION SYSTEMS
Serafino Cicerone , Alessia Di Fonso , Gabriele Di Stefano , Alfredo Navarra
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引用次数: 0

摘要

在移动机器人的背景下,相互可见性是一个众所周知的问题。对于布置在欧几里得平面中的一组n个机器人,它要求在没有碰撞的情况下移动机器人,以实现确保没有三个机器人共线的放置。对于在图上移动的机器人,我们考虑大地互视(GMV)问题。机器人沿着图的边缘移动,不会发生碰撞,从而占据一些顶点,从而确保它们成为成对的测地线,相互可见。这意味着每对机器人之间都有一条最短的路径(即“测地线”),而没有其他机器人沿着这条路径驻留。我们在树和(有限或无限)正方形网格的背景下研究了这个问题,用于在标准的Look–Compute–Move模型下操作的机器人。在这两种情况下,我们都提供了解析算法和形式正确性证明,突出了不同上下文中出现的最相关的特性,同时优化了时间复杂性。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
The geodesic mutual visibility problem: Oblivious robots on grids and trees

The Mutual Visibility is a well-known problem in the context of mobile robots. For a set of n robots disposed in the Euclidean plane, it asks for moving the robots without collisions so as to achieve a placement ensuring that no three robots are collinear. For robots moving on graphs, we consider the Geodesic Mutual Visibility (GMV) problem. Robots move along the edges of the graph, without collisions, so as to occupy some vertices that guarantee they become pairwise geodesic mutually visible. This means that there is a shortest path (i.e., a “geodesic”) between each pair of robots along which no other robots reside. We study this problem in the context of trees and (finite or infinite) square grids, for robots operating under the standard Look–Compute–Move model. In both scenarios, we provide resolution algorithms along with formal correctness proofs, highlighting the most relevant peculiarities arising within the different contexts, while optimizing the time complexity.

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来源期刊
Pervasive and Mobile Computing
Pervasive and Mobile Computing COMPUTER SCIENCE, INFORMATION SYSTEMS-TELECOMMUNICATIONS
CiteScore
7.70
自引率
2.30%
发文量
80
审稿时长
68 days
期刊介绍: As envisioned by Mark Weiser as early as 1991, pervasive computing systems and services have truly become integral parts of our daily lives. Tremendous developments in a multitude of technologies ranging from personalized and embedded smart devices (e.g., smartphones, sensors, wearables, IoTs, etc.) to ubiquitous connectivity, via a variety of wireless mobile communications and cognitive networking infrastructures, to advanced computing techniques (including edge, fog and cloud) and user-friendly middleware services and platforms have significantly contributed to the unprecedented advances in pervasive and mobile computing. Cutting-edge applications and paradigms have evolved, such as cyber-physical systems and smart environments (e.g., smart city, smart energy, smart transportation, smart healthcare, etc.) that also involve human in the loop through social interactions and participatory and/or mobile crowd sensing, for example. The goal of pervasive computing systems is to improve human experience and quality of life, without explicit awareness of the underlying communications and computing technologies. The Pervasive and Mobile Computing Journal (PMC) is a high-impact, peer-reviewed technical journal that publishes high-quality scientific articles spanning theory and practice, and covering all aspects of pervasive and mobile computing and systems.
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