$\Phi$ cluster:基于信息素的机器人群体聚集

F. Arvin, A. E. Turgut, T. Krajník, Salar Rahimi, Ilkin Ege Okay, Shigang Yue, S. Watson, B. Lennox
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引用次数: 32

摘要

本文在BEECLUST算法的基础上,提出了一种基于信息素的聚合方法。我们研究了基于信息素的通信对机器人群体在给定线索的区域定位和聚集效率的影响。特别地,我们评估了信息素蒸发和扩散对蜂群聚集所需时间的影响。在一系列模拟和现实世界的评估试验中,我们证明了用人工信息素增强BEECLUST方法可以更快地聚集时间。
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$\Phi$ Clust: Pheromone-Based Aggregation for Robotic Swarms
In this paper, we proposed a pheromone-based aggregation method based on the state-of-the-art BEECLUST algorithm. We investigated the impact of pheromone-based communication on the efficiency of robotic swarms to locate and aggregate at areas with a given cue. In particular, we evaluated the impact of the pheromone evaporation and diffusion on the time required for the swarm to aggregate. In a series of simulated and real-world evaluation trials, we demonstrated that augmenting the BEECLUST method with artificial pheromone resulted in faster aggregation times.
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