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The Robot Path Planning Based on Improved Artificial Fish Swarm Algorithm

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  • Yi Zhang
  • Guolun Guan
  • Xingchen Pu

Abstract

Path planning is critical to the efficiency and fidelity of robot navigation. The solution of robot path planning is to seek a collision-free and the shortest path from the start node to target node. In this paper, we propose a new improved artificial fish swarm algorithm (IAFSA) to process the mobile robot path planning problem in a real environment. In IAFSA, an attenuation function is introduced to improve the visual of standard AFSA and get the balance of global search and local search; also, an adaptive operator is introduced to enhance the adaptive ability of step. Besides, a concept of inertia weight factor is proposed in IAFSA inspired by PSO intelligence algorithm to improve the convergence rate and accuracy of IAFSA. Five unconstrained optimization test functions are given to illustrate the strong searching ability and ideal convergence of IAFSA. Finally, the ROS (robot operation system) based experiment is carried out on a Pioneer 3-DX mobile robot; the experiment results also show the superiority of IAFSA.

Suggested Citation

  • Yi Zhang & Guolun Guan & Xingchen Pu, 2016. "The Robot Path Planning Based on Improved Artificial Fish Swarm Algorithm," Mathematical Problems in Engineering, Hindawi, vol. 2016, pages 1-11, August.
    • Handle: RePEc:hin:jnlmpe:3297585
    DOI: 10.1155/2016/3297585
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    Cited by:

    1. Xianhua Liu, 2023. "Robot autonomous judgment system based on improved computer algorithm," International Journal of System Assurance Engineering and Management, Springer;The Society for Reliability, Engineering Quality and Operations Management (SREQOM),India, and Division of Operation and Maintenance, Lulea University of Technology, Sweden, vol. 14(2), pages 691-698, April.

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