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Abstract

This research work presents the development of an optimal path planning using elite opposition based bat algorithm (EOBA) for mobile robot, such that the robot avoids obstacle(s) without making contact with them. The bat algorithm (BA) is a nature. inspired meta-heuristic algorithm that works on the basis of the echolocation behavior of bat. It, however, has a poor exploration capability leading to it easily getting stuck in local optima. The EOBA is developed by modifying the BA with the elite opposition-based learning (EOBL) so as to diversify the solution search space and the inertial weight in order to balance its exploration and exploitation. The performance of the proposed path planning technique was compared with that of the standard BA based on the ability to generate an optimal path for a mobile robot in a developed simulation environment. The simulation results showed that EOBA provide an optimal path with minimum elapsed time as compared to that of the standard BA. All simulations were carried out using MATLAB R20136.

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