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An improved beetle antennae search path planning algorithm for vehicles

Author

Listed:
  • Qing Liang
  • Huike Zhou
  • Yafang Yin
  • Wei Xiong

Abstract

With the development of society, the application of mobile robots in industry and life is increasingly extensive, and the local path planning of mobile robots in unknown environments is a problem that needs to be solved. Aiming at the problem that the traditional beetle antennae search (BAS) algorithm can easily fall into local optimum and the optimization accuracy is low, we propose an improved beetle antennae search. It introduces a map safety threshold, the addition of virtual target points, and the smoothing of the path. Map safety threshold means extra space with obstacles at all times, improving path reliability by avoiding collisions. Adding virtual target points reduces situations where the vehicle gets stuck in local optima. The B-spline smoothing path reduces the original path’s straight turns to improve the path’s robustness. The effectiveness and superiority of the algorithm are verified by comparing and testing the existing path planning algorithms through simulation in different environments.

Suggested Citation

  • Qing Liang & Huike Zhou & Yafang Yin & Wei Xiong, 2022. "An improved beetle antennae search path planning algorithm for vehicles," PLOS ONE, Public Library of Science, vol. 17(9), pages 1-15, September.
    • Handle: RePEc:plo:pone00:0274646
    DOI: 10.1371/journal.pone.0274646
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