摘要
针对使用无人机进行城市环境下医药运输的任务分配和航迹规划问题,以需求点坐标和日需求量为依据,以成本最小为目标函数,完成多约束条件的无人机任务分配模型构建,将K-means聚类分析嵌入遗传算法进行无人机起降选址及任务分配求解;在任务分配的基础上选取一条任务线,使用格栅法对该任务线周围的地形、障碍物环境进行空间3D建模,然后引入A^(*)算法对该任务进行最优航迹的搜索;并对三维栅格地图分别进行了基于A^(*)算法、蚁群算法、RRT算法的航迹规划仿真。仿真结果表明:在航迹规划过程中A^(*)算法相较于另外两种算法,航迹更短、搜索回报率更高、航迹更平滑,验证了A^(*)算法的可行性与有效性。
Aiming at the problem of task assignment and trajectory planning for using UAVs for pharmaceutical transportation in urban environments,a UAV task assignment model under multiple constraints based on the coordinates of demand points and daily demand volume was established,with the objective function of minimizing cost.K-means clustering analysis was embedded into the genetic algorithm for solving UAV takeoff and landing site selection and task allocation.A task line was selected on the basis of task assignment,and the grid method was used to perform spatial 3D modeling of the terrain and obstacle environment around the task line.And then,the A^(*) algorithm was introduced to search for the optimal trajectory for this task.The simulation of trajectory planning based on A^(*) algorithm,ACO algorithm and RRT algorithm were carried out respectively on 3D grid map.The simulation results show that in the process of trajectory planning,the A^(*) algorithm has shorter trajectories,higher search return rate and smoother trajectories compared to the other two algorithms,which verifies the feasibility and effectiveness of the A^(*) algorithm.
作者
李航
张小娜
LI Hang;ZHANG Xiaona(Transportation Science and Engineering College,Civil Aviation University of China,Tianjin 300300,China)
出处
《重庆交通大学学报(自然科学版)》
北大核心
2025年第8期83-89,共7页
Journal of Chongqing Jiaotong University(Natural Science)
基金
国家科技部项目(2013GXS4B094)
天津市哲学社会科学规划课题(TJGL18-048)
中央高校基金人文社科重点项目(3122021017)。
关键词
交通运输工程
无人机医药物流
任务分配
航迹规划
k-means聚类分析
A^(*)算法
traffic and transportation engineering
drones for pharmaceutical logistics
task assignment
trajectory planning
K-means clustering analysis
the A^(*)algorithm
作者简介
第一作者:李航(1978-),男,山东冠县人,副教授,主要从事无人机物流系统、航空经济系统分析、航空运输系统优化与决策方面的研究。E-mail:hli@cauc.edu.cn;通信作者:张小娜(2000-),女,河北张家口人,硕士研究生,从事无人机医药物流、航空物流方面的研究。E-mail:2185587584@qq.com。
