Abstract
The shortest/optimal path planning is essential for efficient operation of autonomous vehicle. In this paper a cuckoo search based approach has been implemented for mobile robot navigation in an unknown environment populated by a variety of obstacles. This metaheuristic algorithm is based on the levy flight behavior and brood parasitic behavior of cuckoos. A new objective function has been developed between robot and position of the goal and obstacles present in the environment. Depending upon the objective function value of each nest in swarm, the robot avoids obstacles and proceeds towards goal. The optimal path is generated with this algorithm when robot reaches its goal. Several simulation results are presented here to demonstrate the potential of proposed algorithm.
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Mohanty, P.K., Parhi, D.R. (2013). Cuckoo Search Algorithm for the Mobile Robot Navigation. In: Panigrahi, B.K., Suganthan, P.N., Das, S., Dash, S.S. (eds) Swarm, Evolutionary, and Memetic Computing. SEMCCO 2013. Lecture Notes in Computer Science, vol 8297. Springer, Cham. https://doi.org/10.1007/978-3-319-03753-0_47
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DOI: https://doi.org/10.1007/978-3-319-03753-0_47
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