Revolutionizing swarm dynamics: the role of receptive fields in enhancing convergence and stability

Abstract

The classic Vicsek model, while influential in understanding swarm behavior, has limitations in achieving motion consensus and convergence speed, especially under varying conditions of density and noise. This study aims to introduce a novel receptive field mechanism to the
Vicsek model to enhance its performance in terms of motion consensus and convergence speed within swarms. The modified model divides a particle's surrounding area into excitation and inhibition zones based on distinct functions. This structural modification is designed to enrich evolutionary behavior and improve consensus convergence capabilities. Experimental outcomes indicate that the proposed model achieves faster convergence rates towards motion consensus under various density and noise conditions compared to traditional models.
Specifically, while classic Vicsek models fail to converge to an overall polarization state under high noise levels and exhibit quasi-periodic oscillations, the enhanced model demonstrates stable convergence without oscillatory behavior across both low- and high-noise environments. The findings highlight the superior evolutionary consistency characteristics of the improved model, offering new theoretical and practical insights into the stability and controllability of swarms. This advancement presents significant implications for the development of more robust swarm systems.