PSO-based Search mechanism in dynamic environments: Swarms in Vector Fields

Palina Bartashevich, Luigi Grimaldi, Sanaz Mostaghim
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引用次数: 14

Abstract

This paper presents the Vector Field Map PSO (VFM-PSO) as a collective search algorithm for aerial micro-robots in environments with unknown external dynamics (such as wind). The proposed method is based on a multi-swarm approach and allows to cope with unknown disturbances arising by the vector fields in which the positions and the movements of the particles are highly affected. VFM-PSO requires gathering the information regarding the vector fields and one of our goals is to investigate the amount of the required information for a successful search mechanism. The experiments show that VFM-PSO can reduce the drift and improves the performance of the PSO algorithm despite incomplete information (awareness) about the structure of considered vector fields.
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动态环境中基于pso的搜索机制:向量场中的蜂群
本文提出了矢量场映射粒子群算法(VFM-PSO)作为一种用于未知外部动力(如风)环境下的航空微型机器人的集体搜索算法。该方法基于多群方法,可以处理由矢量场引起的未知干扰,其中粒子的位置和运动受到高度影响。VFM-PSO需要收集有关向量场的信息,我们的目标之一是调查成功搜索机制所需信息的数量。实验表明,尽管所考虑的向量场结构信息不完全(感知),但VFM-PSO算法可以减少漂移,提高PSO算法的性能。
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