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An intelligent navigational strategy for mobile robots in uncertain environments using smart cuckoo search algorithm

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Abstract

This paper presents the implementation of smart cuckoo search (SCS) algorithm for intelligent path planning of mobile robots. A new fitness function is modeled and optimized by SCS algorithm to generate collision free optimal route for the mobile robots. The simulation results are illustrated to verify the ability of robot to deal with different environment conditions and reach to the target in all the time. Also the results obtained using SCS algorithm is compared with results of Adaptive Particle Swarm Optimization (APSO). It is noticed that SCS algorithm showed better results as compared to APSO. Finally the simulation platform results are validated with Khepera-IV mobile robot experimental results and it is revealed that proposed algorithm is valid and feasible in the mobile robot path planning problems.

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Authors and Affiliations

  1. Department of Mechanical Engineering, National Institute of Technology, Yupia, Arunachal Pradesh, 791112, India

    Prases K. Mohanty

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  1. Prases K. Mohanty
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Correspondence to Prases K. Mohanty.

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Appendix

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Fig. 20
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Algorithm flow of the SCS using MATLAB

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Mohanty, P.K. An intelligent navigational strategy for mobile robots in uncertain environments using smart cuckoo search algorithm. J Ambient Intell Human Comput 11, 6387–6402 (2020). https://doi.org/10.1007/s12652-020-02535-5

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