UAV Electric Patrol Path Planning Based on Improved Ant Colony Optimization-A* Algorithm

被引：2
|
作者：
Zhao Changxin [1 ]
Wu Ligang [2 ]
Wang Yiding [1 ]
Zhang Xiao [1 ]
Cui Yandong [1 ]
He Anming [2 ]
Hu Anqiao [3 ]
机构：
[1] State Grid Jiangsu Elect Power Co Ltd, Xuzhou, Jiangsu, Peoples R China
[2] Anhui Jiyuan Software Co Ltd, Hefei, Peoples R China
[3] Hefei Univ Technol, Hefei, Peoples R China
来源：
2022 IEEE INTERNATIONAL CONFERENCE ON ELECTRICAL ENGINEERING, BIG DATA AND ALGORITHMS (EEBDA) | 2022年
关键词：
UAV; Path planning; Electric Power Patrol; Ant colony algorithm;
D O I：
10.1109/EEBDA53927.2022.9744949
中图分类号：
TP39 [计算机的应用];
学科分类号：
081203 ; 0835 ;
摘要：
Due to the control accuracy and the complexity of three-dimensional path planning, it is difficult for multi rotor UAV to locate accurately according to point cloud data. In order to overcome these problems, according to the control accuracy of UAV and taking the minimum how much the energy is consumed as the objective function, an improved ant colony-A* optimization algorithm based on UAV performance and wind speed constrained path planning model is established in this paper. The improved ant colony-A* algorithm is used to find the approximate optimal trajectory on the premise of covering all shooting points. The simulation results show that compared with the air transmission line UAV patrol image shooting manual, the how much the energy is consumed of the improved algorithm is greatly reduced.
引用
收藏
页码：1374 / 1380
页数：7
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