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

被引：0
|
作者：
Yu Q. [1 ]
Xu Z. [1 ]
Duan N. [1 ]
Xu M. [1 ]
Cheng Y. [2 ]
机构：
[1] College of Electrical Engineering and Automation, Jiangsu Normal University, Xuzhou
[2] Jiangsu Dandelion UAV Company, Xuzhou
来源：
Hangkong Xuebao/Acta Aeronautica et Astronautica Sinica | 2023年 / 44卷 / 12期
基金：
中国国家自然科学基金;
关键词：
ant colony optimization; endurance constraint; full coverage operation; path planning; unmanned aerial vehicle;
D O I：
10.7527/S1000-6893.2022.27856
中图分类号：
学科分类号：
摘要：
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. © 2023 AAAS Press of Chinese Society of Aeronautics and Astronautics. All rights reserved.
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