Abstract
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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Najd Ataei, H., Ziarati, K., Eghtesad, M. (2013). A BSO-Based Algorithm for Multi-robot and Multi-target Search. In: Ali, M., Bosse, T., Hindriks, K.V., Hoogendoorn, M., Jonker, C.M., Treur, J. (eds) Recent Trends in Applied Artificial Intelligence. IEA/AIE 2013. Lecture Notes in Computer Science(), vol 7906. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-38577-3_32
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DOI: https://doi.org/10.1007/978-3-642-38577-3_32
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