A BSO-Based Algorithm for Multi-robot and Multi-target Search

Swarm robots are used in robotic applications where it is difficult or impossible for a single robot to accomplish a task. In this paper, we study multi-robot, multi-target search problem in an unknown environment. Our goal is to use a group of distributed cooperative mobile robots to find position of an object which is emitting the strongest intensity of radio frequency in the environment. We propose a novel algorithm based on Bee Swarm Optimization (BSO) which is able to automatically find the object. Our experimental results, simulated on a set of random benchmarks, show that the algorithm is able to outperform the state-of-the-art techniques, in particular Particle Swarm Optimization (PSO). We show that our algorithm can be 50.6% more effective for this application in comparison to PSO.

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