A Foundational Framework for Certified Impossibility Results with Mobile Robots on Graphs

Thibaut Balabonski, Robin Pelle, Lionel Rieg, S. Tixeuil
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引用次数: 13

Abstract

Swarms of mobile robots recently attracted the focus of the Distributed Computing community. One of the fundamental problems in this context is that of exploration: the robots must coordinate to visit all locations that are reachable from their initial positions. Despite its apparent simplicity, this problem proved quite hard to characterise fully, due to many model variants, leading to informal error-prone reasoning. Over the past few years, a significant effort permitted to set up a formal framework, relying on the Coq proof assistant, which was used to provide certified results when robots evolve in a continuous bi-dimensional Euclidean space. However, the most challenging issues with exploration arise in the discrete setting (a.k.a. graph), where locations are modeled as vertices and where edges between vertices denote the ability for a robot to move from one location to the next. We present a formal model to tackle problems and reason about robot algorithms arising in the discrete setting. Our approach extends and generalises previous research efforts focusing on the continuous model. As case studies, we consider fundamental impossibility results for exploration with stop in the discrete model. To our knowledge, those are the first certified results in this context. This framework paves the way for a general certification workflow dedicated to mobile robots on graphs.
图上移动机器人证明不可能结果的基本框架
最近,成群的移动机器人引起了分布式计算社区的关注。在这种情况下,一个基本问题是探索:机器人必须协调访问从初始位置可到达的所有位置。尽管这个问题看起来很简单,但由于许多模型变体,导致了非正式的容易出错的推理,因此很难完全描述这个问题。在过去的几年里,一个重要的努力允许建立一个正式的框架,依赖于Coq证明助手,当机器人在连续的二维欧几里得空间中进化时,它被用来提供认证的结果。然而,探索中最具挑战性的问题出现在离散设置(又名图形)中,其中位置被建模为顶点,顶点之间的边表示机器人从一个位置移动到下一个位置的能力。我们提出了一个形式化的模型来解决离散环境下机器人算法产生的问题和原因。我们的方法扩展和推广了以前的研究工作,重点放在连续模型上。作为案例研究,我们考虑了离散模型中停止勘探的基本不可能结果。据我们所知,这些是在这方面首次得到证实的结果。该框架为专用于图形移动机器人的通用认证工作流铺平了道路。
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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