沈阳航空航天大学学报2025，Vol.42Issue(1)：57-65,9.DOI:10.3969/j.issn.2095-1248.2025.01.006
基于蚁群优化算法的无人直升机三维航迹规划
Three-dimensional flight path planning of unmanned autonomous heli-copter based on ant colony optimization algorithm
摘要
Abstract
Taking the unmanned autonomous helicopter(UAH)for campus patrol as an example,ai-ming at the problem of three-dimensional flight path planning during the low-altitude flight of UAH,a three-dimensional multilevel flight path planning algorithm based on ant colony optimization(ACO)algorithm was proposed.Firstly,according to the constraint conditions of the environment and the performance characteristics of UAH,the campus environment was modeled as a three-dimensional raster model,and the distribution of static obstacles was highly stratified to build a two-dimensional raster map.Then,two-dimensional flight path planning was carried out based on the ant colony optimization algorithm with improved pheromone updating mechanism.When the unmanned autonomous helicopter encountered static or dynamic obstacles in front of it,its vertical take-off and landing characteristics were utilized to realize the transformation of the altitude layer.In the new altitude layer,the ant colony optimization algorithm was used to replan the flight path,and finally the three-dimensional flight path planning of the unmanned autonomous helicopter's low-altitude flight task was realized.The simulation results show that the ACO algorithm with improved pheromone updating mechanism can realize the 3D flight path planning of unmanned autonomous helicopter at low altitude better.关键词
无人直升机/蚁群优化/三维栅格/航迹规划/高度层Key words
unmanned autonomous helicopter/ant colony optimization/three-dimensional raster/flight path planning/altitude layer分类
计算机与自动化引用本文复制引用
卢艳军,薄乐,高子惠,赵国佳..基于蚁群优化算法的无人直升机三维航迹规划[J].沈阳航空航天大学学报,2025,42(1):57-65,9.基金项目
国家重点研发计划项目(项目编号:2022YFC2903805) （项目编号:2022YFC2903805）
辽宁省教育厅重点攻关项目(项目编号:LJKZZ20220030). （项目编号:LJKZZ20220030）
