Distributed Adaptation in Multi-robot Search Using Particle Swarm Optimization

Authors:
Jim Pugh;Alcherio Martinoli
Affiliations:
Swarm-Intelligent Systems Group, École Polytechnique Fédérale de Lausanne, Lausanne, Switzerland 1015;Swarm-Intelligent Systems Group, École Polytechnique Fédérale de Lausanne, Lausanne, Switzerland 1015
Venue:
SAB '08 Proceedings of the 10th international conference on Simulation of Adaptive Behavior: From Animals to Animats
Year:
2008

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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.