基于机器学习的农用飞行器路径规划系统设计  

Design of Path Planning System for Agricultural Aircraft Based on Machine Learning

作　　者：赵海发 Zhao Haifa(Jiyuan Vocational and Technical College, Jiyuan 459000,China)

机构地区：[1]济源职业技术学院,河南济源459000

出　　处：《农机化研究》2022年第4期32-36,共5页Journal of Agricultural Mechanization Research

基　　金：国家自然科学基金项目(51375145)。

摘　　要：基于作业空间模型及更新和飞行器机动性能约束,搭建了农用飞行器路径规划环境模型,并采用改进人工势能的机器学习算法,结合农用飞行器路径规划环境模型和障碍物检测模块,实现了农用飞行器路径规划的最优化。MatLab仿真结果表明:农用飞行器路径规划系统能够识别障碍物的位置和边界信息,并能快速制定出最优的飞行路径,指引农用飞行器顺利到达目标点。It firstly built the path planning environment model of agricultural vehicle from the working space model and the constraints of updating and maneuvering performance of the vehicle.It used the machine learning algorithm based on the improved artificial potential energy to realize the optimization of the path planning of agricultural vehicle combining with the path planning environment model of agricultural vehicle and the obstacle detection module.Matlab simulation results show that the path planning system of agricultural vehicles can identify the location and boundary information of obstacles,and can quickly develop the optimal flight path to guide agricultural vehicles to reach the target point smoothly.

关 键 词：农用飞行器 路径规划 改进人工势能 机器学习 MATLAB 

分 类 号：S251[农业科学—农业机械化工程] TP181[农业科学—农业工程]