蚁群优化算法
运动规划
计算机科学
路径(计算)
能量(信号处理)
算法
数学优化
人工智能
机器人
数学
统计
程序设计语言
作者
Changxin Zhao,Wu Ligang,Yiding Wang,Xiao Zhang,Cui Yandong,He Anming,Hu Anqiao
标识
DOI:10.1109/eebda53927.2022.9744949
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.
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