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Target searching in unknown environment of multi-robot system using a hybrid particle swarm optimization
journal contribution
posted on 2018-07-15, 00:00 authored by Bahareh NakisaBahareh Nakisa, M N Rastgoo, M Z A Nazri, M J Nordin© 2005 – ongoing JATIT & LLS. Target searching in unknown environment using multi-robot search systems has received increasing attention in recent years. Particle Swarm Optimization (PSO) has applied successfully on multi-robot target searching system. However, this algorithm suffer from premature convergence problem and cannot escape from the local optima. It is, therefore, important to have an efficient method to escape from the local optima and create and efficient balance between exploitation and exploration. In this study, we propose a new method based on PSO algorithm (ATREL-PSO) to find the target in unknown environment using multi-robot system within a limited time. This novel algorithm is demonstrated to escape from the local optima and create an efficient balance between exploration and exploitation to reach the target faster. The concept of attraction, repulsion and the combination of repulsion and attraction enhancing the search exploration, and when the robot get closer to the target it should forget the PSO concept and apply the local search method to reach the target faster. Experimental results obtained in a simulated environment show that biological and sociological inspiration could be useful to meet the challenges of robotic applications that can be described as optimization problems.
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Journal
Journal of Theoretical and Applied Information TechnologyVolume
96Issue
13Pagination
4055 - 4065Publisher
Asian Research Publication NetworkLocation
Islamabad, PakistanISSN
1817-3195eISSN
1817-3195Language
engPublication classification
C1.1 Refereed article in a scholarly journalUsage metrics
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