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Fault-Tolerant and Self-stabilizing Mobile Robots Gathering: Feasibility Study

机译:容错和自稳定的移动机器人聚会:可行性研究

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Gathering is a fundamental coordination problem in cooperative mobile robotics. In short, given a set of robots with arbitrary initial location and no initial agreement on a global coordinate system, gathering requires that all robots, following their algorithm, reach the exact same but not predetermined location. Gathering is particularly challenging in networks where robots are oblivious (i.e., stateless) and the direct communication is replaced by observations on their respective locations. Interestingly any algorithm that solves gathering with oblivious robots is inherently self-stabilizing. In this paper, we significantly extend the studies of deterministic gathering feasibility under different assumptions related to synchrony and faults (crash and Byzantine). Unlike prior work, we consider a larger set of scheduling strategies, such as bounded schedulers, and derive interesting lower bounds on these schedulers. In addition, we extend our study to the feasibility of probabilistic gathering in both fault-free and fault-prone environments. To the best of our knowledge our work is the first to address the gathering from a probabilistic point of view.
机译:收集是协作移动机器人中的一个基本协调问题。简而言之,给定一组具有任意初始位置且在全局坐标系上没有初始协议的机器人,采集要求所有机器人按照其算法到达完全相同但并非预定的位置。在机器人遗忘(即无状态)且直接通信被其各自位置的观察代替的网络中,聚集尤其具有挑战性。有趣的是,任何可以解决遗忘机器人的算法本质上都是自稳定的。在本文中,我们极大地扩展了在与同步和故障(崩溃和拜占庭式)相关的不同假设下确定性收集可行性的研究。与先前的工作不同,我们考虑使用一组更大的调度策略,例如有界调度器,并在这些调度器上得出有趣的下限。另外,我们将研究扩展到在无故障和易故障环境中概率收集的可行性。据我们所知,我们的工作是第一个从概率角度解决聚会的工作。

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