Easily scalable algorithms for dispersing autonomous robots

M. Siebold, J. Hereford
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引用次数: 7

Abstract

This paper describes three new algorithms for dispersing a swarm of bots throughout a search space. We assume that the bots do not have a central coordinating agent and we want to have no (or few) inter-bot communications so that the algorithms can scale to large swarm sizes. We simulated the three new dispersion algorithms plus two other random-walk based dispersion algorithms on five different search spaces. Each of the five algorithms was tested with swarm sizes from three to fifty bots. For swarm sizes larger than ten, we found that the minimize-intensity algorithm, which is based on decaying signal strengths, worked best. For small swarm sizes, the dispersion algorithm based on the dispersion of gas particles performed best.
易于扩展的分散自主机器人算法
本文描述了在搜索空间中分散机器人群的三种新算法。我们假设机器人没有中央协调代理,并且我们希望机器人之间没有(或很少)通信,以便算法可以扩展到大型群体规模。我们在五个不同的搜索空间上模拟了三种新的色散算法和另外两种基于随机行走的色散算法。这五种算法中的每一种都用3到50个机器人进行了测试。对于大于10的蜂群,我们发现基于衰减信号强度的最小强度算法效果最好。对于较小的群体,基于气体粒子分散的分散算法效果最好。
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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