Electronics and Electrical Engineering and Control

Coverage operation path planning of UAV with endurance constraints based on improved ACO

  • Quanyou YU ,
  • Zhizheng XU ,
  • Na DUAN ,
  • Mimi XU ,
  • Yi CHENG
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  • 1.College of Electrical Engineering and Automation,Jiangsu Normal University,Xuzhou 221000,China
    2.Jiangsu Dandelion UAV Company,Xuzhou 221000,China
E-mail: xuzz@jsnu.edu.cn

Received date: 2022-07-26

  Revised date: 2022-09-13

  Accepted date: 2023-01-28

  Online published: 2023-02-06

Supported by

National Natural Science Foundation of China(62173166);Universities Natural Science Research Project of Jiangsu Province(20KJB510047);Fundamental Research Program of Xuzhou City(KC22053);Postgraduate Research and Practice Innovation Program of Jiangsu Province(SJCX21_1130)

Abstract

This paper studies the path planning problem of full coverage operation of electric multi-rotor UAVs with endurance constraint. Firstly, a mathematical model of path planning for UAV full coverage operation with endurance constraints is established based on the sweep method. Then, an improved Ant Colony Optimization (ACO) is proposed for handling the dynamic change of path node topology in the path planning model. In the improved ACO, the assessment mechanism of UAV’s return time and calculation method of the return point is provided. A dynamic local distance matrix, together with a pheromone updating mechanism based on the rolling weight weighted sum, is designed, considering both global and local heuristic information in the optimization process. Finally, two examples of multi-field operation tasks with regular and complex terrains are used to verify the effectiveness and advantage of the proposed algorithm. The results show that, compared with the other four algorithms, the proposed algorithm can reduce the length of the shifting path by at least 1.8% and 11.4% on the regular terrain and complex terrain, respectively.

Cite this article

Quanyou YU , Zhizheng XU , Na DUAN , Mimi XU , Yi CHENG . Coverage operation path planning of UAV with endurance constraints based on improved ACO[J]. ACTA AERONAUTICAET ASTRONAUTICA SINICA, 2023 , 44(12) : 327856 -327856 . DOI: 10.7527/S1000-6893.2022.27856

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