异步自主机器人在网格上的最优任意图案形成

Rory Hector, Gokarna Sharma, R. Vaidyanathan, J. Trahan
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引用次数: 5

摘要

我们考虑了$N$自主移动机器人的分布式设置,该机器人遵循带灯机器人模型或经典遗忘机器人模型,以Look-Compute-Move (LCM)周期运行。对于灯光模型,我们假设能见度受到阻碍,因此如果第三个机器人在连接它们的直线上位于它们之间,则机器人无法看到另一个机器人。相比之下,我们在经典模型中假设无阻碍的可见性,因此机器人可以看到所有其他机器人,而不管它们的位置如何。此外,我们考虑了嵌入在二维欧几里得平面中的基于网格的地形,该地形将每个机器人的运动限制在其当前位置的四个相邻网格点之一。这种网格设置是对二维真实平面的自然离散化,将机器人群模型向适用性更强的方向进行了扩展。任意模式形成问题是重新定位$N$机器人(从网格上任意但不同的初始位置开始)以形成作为输入的任意目标模式。本文给出了两种异步任意模式生成算法,一种基于光照模型,另一种基于经典模型。算法性能的关键指标包括每个机器人所花费的时间和移动次数。两种算法在$O(\max\{D^{i}, D^{p}\})$时间内运行,每个机器人的移动次数为$O(\max\{D^{i}, D^{p}\})$,其中$D^{i}$和$D^{p}$分别是初始配置和模式配置的直径。灯光模型的算法使用$O(1)$颜色。我们还证明了任意模式形成算法在目标模式上不允许缩放时的时间下界$\Omega(\max\{D^{i}, D^{p}\})$。因此,我们的算法是最优的w.r.t.时间。此外,我们的算法也是最优的w.r.t.移动的数量给定的移动数量$\Omega(\max\{D^{i}, D^{p}\})$的现有下界。总之,我们的结果表明,在任意图案形成的经典模型中,有灯提供了一种对无阻碍可见性要求的权衡。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Optimal Arbitrary Pattern Formation on a Grid by Asynchronous Autonomous Robots
We consider the distributed setting of $N$ autonomous mobile robots that operate in Look-Compute-Move (LCM) cycles following either the robots with lights model or the classical oblivious robots model. For the lights model, we assume obstructed visibility so that a robot cannot see another robot if a third robot is positioned between them on the straight line connecting them. In contrast, we assume unobstructed visibility in the classical model so that a robot sees all others irrespective of their positions. In addition, we consider a grid-based terrain embedded in the 2-dimensional Euclidean plane that restricts each robot's movement to one of the four neighboring grid points from its current position. This grid setting is a natural discretization of the 2-dimensional real plane and extends the robot swarm model in directions of greater applicability. The Arbitrary Pattern Formationproblem is to relocate the $N$ robots (starting at arbitrary but distinct initial positions on a grid) to form an arbitrary target pattern given as input. In this paper, we provide two asynchronous algorithms for Arbitrary Pattern Formation, one on the lights model and another on the classical model. Key measures of the algorithms' performance include the time taken and the number of moves by each robot. Both algorithms run in $O(\max\{D^{i}, D^{p}\})$ time with $O(\max\{D^{i}, D^{p}\})$ moves by each robot, where $D^{i}$ and $D^{p}$, respectively, are the diameters of the initial and pattern configurations. The algorithm for the lights model uses $O(1)$ colors. We also prove a lower bound of $\Omega(\max\{D^{i}, D^{p}\})$ for time for any Arbitrary Pattern Formationalgorithm if scaling is not allowed on the target pattern. Therefore, our algorithms are optimal w.r.t. time. Furthermore, our algorithms are also optimal w.r.t. the number of moves given the existing lower bound of $\Omega(\max\{D^{i}, D^{p}\})$ on the number of moves. In sum, our results show that having lights provides a trade-off on the unobstructed visibility requirement in the classical model for Arbitrary Pattern Formation.
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