基于蚁群优化算法的无人直升机三维航迹规划

卢艳军; 薄乐; 高子惠; 赵国佳

doi:10.3969/j.issn.2095-1248.2025.01.006

沈阳航空航天大学学报 ›› 2025, Vol. 42 ›› Issue (1) : 57 -65. DOI: 10.3969/j.issn.2095-1248.2025.01.006

信息科学与工程

基于蚁群优化算法的无人直升机三维航迹规划

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Three-dimensional flight path planning of unmanned autonomous helicopter based on ant colony optimization algorithm

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摘要

以校园巡视无人直升机（unmanned autonomous helicopter，UAH）为例，针对无人直升机低空飞行过程中三维航迹规划的问题，提出了一种基于蚁群优化（ant colony optimization，ACO）算法的三维多层次航迹规划算法。首先，根据环境和UAH自身性能特点的约束条件对校园环境进行三维栅格建模，并对静态障碍物的分布情况进行高度分层，分层建立二维栅格地图。然后，采用改进信息素更新机制的ACO算法进行二维航迹规划。当无人直升机前方遇到静态或动态障碍物时，利用其垂直起降的特点实现高度层的变换。在新的高度层中再利用蚁群优化算法重新规划航迹，最终实现无人直升机低空飞行任务的三维航迹规划。仿真实验结果表明，改进信息素更新机制的ACO三维航迹规划算法能较好地实现无人直升机在低空飞行时的三维航迹规划。

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.