基于相似离子间斥力的RDPSO多样性增强机器人目标搜索

Masoud Dadgar, M. Couceiro, A. Hamzeh
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引用次数: 9

摘要

本文研究了多机器人目标搜索问题。我们通过提出一种基于相似离子之间的排斥机制来提高收敛速度的新机制,为当前最先进的技术做出了贡献。在本文中,我们将机器人视为离子,其中采用的方法的主要目的是保持机器人之间的多样性水平稳定。该机制将应用于粒子群优化(PSO)方法,称为机器人达尔文粒子群优化(RDPSO)。这一改进是为了加快先前提出的方法的速度,并提供准确的搜索结果。结果表明,该方法在速度和搜索结果方面都具有优越性。此外,当机器人数量减少时,与其他方法相比,所提出的方法表现出更优越的性能。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
RDPSO diversity enhancement based on repulsion between similar ions for robotic target searching
In this paper, we studied the problem of multi-robot target searching. We contributed to the current state-of-the-art by proposing a novel mechanism to increase the convergence speed based on a repulsion mechanism between similar ions. In this article, we perceive robots as ions, wherein the main purpose of the adopted approach is to keep the level of diversity among the robots stable. This mechanism will be applied to a particle swarm optimization (PSO) approach, denoted as Robotic Darwinian PSO (RDPSO). This improvement was done to speed up the previously proposed approaches and to provide accurate search results. The results depict the superiority of the proposed approach both in terms of speed and search result. Also, the proposed approach shows a superior performance when it is compared with other approaches as the number of robots decreases.
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