Collective Behavior of Robots Swarm

N. Hassan
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Abstract

a great interest has evolved recently in the study and synthesis of cooperative robots with decentralized control. The basic problem is the development of efficient algorithms that could be inspired from the behavior of social insects. This paper develops from different perspective; the theory of decentralized discrete control systems. This leads to a little increase in the computational complexity in each individual, still non-intelligent, robot. Swarm intelligence appears as a result of the mutual control signals that replace coordination signals in usual centralized control systems. The study of asymptotic stability and the convergence to the global goal follows directly from the stability of algorithms derived within system theory and are reached stepwise in an efficient way. Through the paper we derive the necessary algorithms and procedures and finally we introduce the experimental results that validate the developed theory.
机器人群的集体行为
近年来,人们对分散控制的协作机器人的研究和综合产生了极大的兴趣。最基本的问题是如何从群居昆虫的行为中得到启发,开发出高效的算法。本文从不同的角度展开;分散离散控制系统理论。这将导致每个个体的计算复杂性略有增加,仍然是非智能的机器人。群智能的出现是由于在通常的集中控制系统中,相互控制信号取代了协调信号。渐近稳定性和全局目标收敛性的研究直接来源于系统理论中导出的算法的稳定性,并以一种有效的方式逐步达到。通过本文推导了必要的算法和步骤,最后介绍了实验结果,验证了所建立的理论。
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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