基于改进蚁群算法的无人机三维路径规划研究  

Research on 3D Path Planning of Unmanned Aerial Vehicles Based onImproved Ant Colony Algorithm

作　　者：陆璐 孙昱浩 孙启光 LU Lu;SUN Yuhao;SUN Qiguang(Shandong Jiaotong University,Weihai 264200,Shandong,China)

机构地区：[1]山东交通学院,山东威海264200

出　　处：《广东交通职业技术学院学报》2025年第1期46-51,114,共7页Journal of Guangdong Communication Polytechnic

基　　金：山东交通学院博士科研启动基金“航海虚拟仿真中复杂场景动态模拟”(编号:BS2017060)。

摘　　要：无人机在自主飞行过程中容易受地形、环境等因素的影响。为了确保无人机能够安全完成飞行任务,对无人机路径规划进行研究。由于传统的蚁群算法在无人机三维路径规划中易陷于局部最优,通过引入方向因子改进启发式函数,使算法搜索具有方向性。同时以最短路径为目标,提出一种改进信息素更新规则,跳出局部最优,加快收敛速度。本文通过栅格化的方法建立三维路径规划空间,经改进前后仿真实验结果对比,改进后的效果明显优于改进前,验证了基于改进蚁群算法的无人机三维路径规划的有效性。Unmanned aerial vehicles(UAV)are easily affected by the factors such as terrain and environment during autonomous flight.In order to ensure the safe completion of flight missions by UAV,this paper conducts research on UAV path planning.Due to the tendency of traditional ant colony algorithm to fall into local optima in 3D path planning of unmanned aerial vehicles,the heuristic function is improved by introducing directional factors to make the algorithm search directional.At the same time,with the shortest path as the goal,an improved pheromone update rule is proposed to break out of local optima and accelerate convergence speed.This paper establishes a three-dimensional path planning space through rasterization method,and compares the simulation experimental results before and after improvement.The improved effect is significant,verifying the effectiveness of the improved ant colony algorithm for UAV three-dimensional path planning.

关 键 词：蚁群算法 三维路径规划 无人机 栅格化 

分 类 号：V279[航空宇航科学与技术—飞行器设计]