An adaptive particle swarm optimization algorithm for distributed search and collective cleanup in complex environment

Y. Cai, Z. Chen, J. Li, Qing Li, H. Min

Research output: Journal article publicationJournal articleAcademic researchpeer-review

2 Citations (Scopus)

Abstract

Distributed coordination is critical for a multirobot system in collective cleanup task under a dynamic environment. In traditional methods, robots easily drop into premature convergence. In this paper, we propose a Swarm Intelligence based algorithm to reduce the expectation time for searching targets and removing. We modify the traditional PSO algorithm with a random factor to tackle premature convergence problem, and it can achieve a significant improvement in multi-robot system. It performs well even in a obstacle environment. The proposed method has been implemented on self-developed simulator for searching task. The simulation results demonstrate the feasibility, robustness, and scalability of our proposed method compared to previous methods. © 2013 Yi Cai et al.
Original languageEnglish
Article number560579
JournalInternational Journal of Distributed Sensor Networks
Volume2013
DOIs
Publication statusPublished - 1 Jan 2013
Externally publishedYes

ASJC Scopus subject areas

  • Engineering(all)
  • Computer Networks and Communications

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