Multi-robot, multi-target particle swarm optimization search in noisy wireless environments

Authors:
Kurt Derr;Milos Manic
Affiliations:
Idaho National Laboratory, Idaho Falls, ID;Department of Computer Science, University of Idaho at Idaho Falls, Idaho Falls, ID
Venue:
HSI'09 Proceedings of the 2nd conference on Human System Interactions
Year:
2009

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Abstract

Multiple small robots (swarms) can work together using Particle Swarm Optimization (PSO) to perform tasks that are difficult or impossible for a single robot to accomplish. The problem considered in this paper is exploration of an unknown environment with the goal of finding a target(s) at an unknown location(s) using multiple small mobile robots. This work demonstrates the use of a distributed PSO algorithm with a novel adaptive RSS weighting factor to guide robots for locating target(s) in high risk environments. The approach was developed and analyzed on multiple robot single and multiple target search. The approach was further enhanced by the multi-robot-multi-target search in noisy environments. The experimental results demonstrated how the availability of radio frequency signal can significantly affect robot search time to reach a target.