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Integrated optimization of unmanned aerial vehicle task allocation and path planning under steady wind

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  • He Luo
  • Zhengzheng Liang
  • Moning Zhu
  • Xiaoxuan Hu
  • Guoqiang Wang

Abstract

Wind has a significant effect on the control of fixed-wing unmanned aerial vehicles (UAVs), resulting in changes in their ground speed and direction, which has an important influence on the results of integrated optimization of UAV task allocation and path planning. The objective of this integrated optimization problem changes from minimizing flight distance to minimizing flight time. In this study, the Euclidean distance between any two targets is expanded to the Dubins path length, considering the minimum turning radius of fixed-wing UAVs. According to the vector relationship between wind speed, UAV airspeed, and UAV ground speed, a method is proposed to calculate the flight time of UAV between targets. On this basis, a variable-speed Dubins path vehicle routing problem (VS-DP-VRP) model is established with the purpose of minimizing the time required for UAVs to visit all the targets and return to the starting point. By designing a crossover operator and mutation operator, the genetic algorithm is used to solve the model, the results of which show that an effective UAV task allocation and path planning solution under steady wind can be provided.

Suggested Citation

  • He Luo & Zhengzheng Liang & Moning Zhu & Xiaoxuan Hu & Guoqiang Wang, 2018. "Integrated optimization of unmanned aerial vehicle task allocation and path planning under steady wind," PLOS ONE, Public Library of Science, vol. 13(3), pages 1-24, March.
    • Handle: RePEc:plo:pone00:0194690
    DOI: 10.1371/journal.pone.0194690
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    References listed on IDEAS

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    Cited by:

    1. ZhengQiang Xiong & Qiuze Yu & Tao Sun & Wen Chen & Yuhao Wu & Jie Yin, 2020. "Super-resolution reconstruction of real infrared images acquired with unmanned aerial vehicle," PLOS ONE, Public Library of Science, vol. 15(6), pages 1-18, June.
    2. Vinícius Antonio Battagello & Nei Yoshihiro Soma & Rubens Junqueira Magalhães Afonso, 2020. "Computational load reduction of the agent guidance problem using Mixed Integer Programming," PLOS ONE, Public Library of Science, vol. 15(6), pages 1-45, June.

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