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

作　　者：刘晓芬[1] 吴传淑 张紫瑞 陈珏先 Liu Xiaofen;Wu Chuanshu;Zhang Zirui;Chen Juexian(Department of Basic Course,Logistics University of PAP,Tianjin 300309,China;Equipment Support Department,Logistics University of PAP,Tianjin 300309,China)

机构地区：[1]武警后勤学院基础部,天津300309 [2]武警后勤学院装备保障系,天津300309

出　　处：《兵工自动化》2025年第4期107-112,共6页Ordnance Industry Automation

基　　金：武警后勤学院理论研究项目(WHL202307)。

摘　　要：针对无人机在有威胁战场环境下的2维和3维路径规划问题,提出一种基于粒子群(particleswarm optimization,PSO)和人工蜂群(artificialbeecolony,ABC)混合算法。根据B样条可以修改局部飞行轨迹的特点,引入非均匀B样条曲线优化拐点处的路径,使得到的路径更加平滑,无人机机动转弯相对更少。结果表明:该研究提高了无人机飞行的安全性和高效性,便于无人机的飞行控制跟踪实现。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 

分 类 号：V279[航空宇航科学与技术—飞行器设计]