兵工自动化2025，Vol.44Issue(4)：107-112,6.DOI:10.7690/bgzdh.2025.04.022
基于粒子群和蜂群算法的无人机路径规划
UAV Path Planning Based on Particle Swarm Optimization and Artificial Bee Colony Algorithm
摘要
Abstract
A hybrid algorithm based on particle swarm optimization(PSO)and artificial bee colony(ABC)is proposed for 2D and 3D path planning of unmanned aerial vehicle(UAV)in threatening battlefield environment.According to the characteristic that B-spline can modify the local flight trajectory,the non-uniform B-spline curve is introduced to optimize the path at the inflection point,so that the obtained path is smoother and the UAV maneuvers are relatively less.The results show that the research improves the safety and efficiency of UAV flight,and is convenient for the realization of UAV flight control and tracking.关键词
路径规划/B样条/粒子群算法/人工蜂群算法/飞行控制Key words
path planning/B-spline/particle swarm optimization/artificial bee colony algorithm/flight control分类
航空航天引用本文复制引用
刘晓芬,吴传淑,张紫瑞,陈珏先..基于粒子群和蜂群算法的无人机路径规划[J].兵工自动化,2025,44(4):107-112,6.基金项目
武警后勤学院理论研究项目(WHL202307) （WHL202307）
