Distributed Adaptation in Multi-robot Search Using Particle Swarm Optimization

  • Jim Pugh
  • Alcherio Martinoli
Conference paper

DOI: 10.1007/978-3-540-69134-1_39

Part of the Lecture Notes in Computer Science book series (LNCS, volume 5040)
Cite this paper as:
Pugh J., Martinoli A. (2008) Distributed Adaptation in Multi-robot Search Using Particle Swarm Optimization. In: Asada M., Hallam J.C.T., Meyer JA., Tani J. (eds) From Animals to Animats 10. SAB 2008. Lecture Notes in Computer Science, vol 5040. Springer, Berlin, Heidelberg

Abstract

We present an adaptive strategy for a group of robots engaged in the localization of multiple targets. The robotic search algorithm is inspired by chemotaxis behavior in bacteria, and the algorithmic parameters are updated using a distributed implementation of the Particle Swarm Optimization technique. We explore the efficacy of the adaptation, the impact of using local fitness measurements to improve global fitness, and the effect of different particle neighborhood sizes on performance. The robustness of the approach in non-static environments is tested in a time-varying scenario.

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Copyright information

© Springer-Verlag Berlin Heidelberg 2008

Authors and Affiliations

  • Jim Pugh
    • 1
  • Alcherio Martinoli
    • 1
  1. 1.Swarm-Intelligent Systems GroupÉcole Polytechnique Fédérale de LausanneLausanneSwitzerland

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