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A smart path planner for wheeled mobile robots using adaptive particle swarm optimization

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Journal of the Brazilian Society of Mechanical Sciences and Engineering Aims and scope Submit manuscript

Abstract

Finding the shortest path to the destination is a vital need for autonomous mobile robots. In this article, a smart adaptive particle swarm optimization (APSO) algorithm is proposed for robot path planning. It allows the robot to reach the target point with the shortest possible path and to avoid the obstacles safely in uncertain environments. A new objective function is derived with distance function and a path smoothening parameter is integrated to avoid sharp turns. The results of the proposed method rely on computer simulation and real robot experimentation in different environments. It is proved that they are in good agreement. A comparative study between the proposed algorithm and various other algorithms is also presented. The results showed that the proposed smart algorithm is capable of successfully avoiding various types of obstacles including the local minima situation.

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Authors and Affiliations

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

    Prases K. Mohanty & Harshal S. Dewang

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  1. Prases K. Mohanty
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  2. Harshal S. Dewang
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Correspondence to Prases K. Mohanty.

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Technical Editor: Adriano Almeida Gonçalves Siqueira.

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Mohanty, P.K., Dewang, H.S. A smart path planner for wheeled mobile robots using adaptive particle swarm optimization. J Braz. Soc. Mech. Sci. Eng. 43, 101 (2021). https://doi.org/10.1007/s40430-021-02827-7

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