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arXiv 1409.4863cs.MAcs.RO
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机器人网络中分布式决策性能的基本限制

On the fundamental limitations of performance for distributed decision-making in robotic networks

Stanford University(斯坦福大学)

Federico Rossi, Marco Pavone

摘要:

本文研究了机器人网络中分布式决策性能的基本限制。我们考虑的决策问题的类包括一些典型的问题,如基于平均的共识以及分布式优化,领导者选举,多数表决,MAX,MIN和逻辑公式。首先,我们提出了一个正式的机器人网络上的分布式计算模型,是基于I/O自动机的概念,并受到计算机科学文献的启发,分布式计算集群。然后,我们提出了一些关于时间,消息和字节复杂性的界限,我们使用这些界限来讨论一些分布式决策方法的相对性能。从方法论的角度来看,我们的工作揭示了由计算机科学和控制社区开发的工具之间的关系分布式算法的主题。

英文摘要:

This paper studies fundamental limitations of performance for distributed decision-making in robotic networks. The class of decision-making problems we consider encompasses a number of prototypical problems such as average-based consensus as well as distributed optimization, leader election, majority voting, MAX, MIN, and logical formulas. We first propose a formal model for distributed computation on robotic networks that is based on the concept of I/O automata and is inspired by the Computer Science literature on distributed computing clusters. Then, we present a number of bounds on time, message, and byte complexity, which we use to discuss the relative performance of a number of approaches for distributed decision-making. From a methodological standpoint, our work sheds light on the relation between the tools developed by the Computer Science and Controls communities on the topic of distributed algorithms.

机构、总结、中文摘要均由AI分析而来,可能存在错误,请以论文正文为准。

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