摘要
首先从PCA技术和SVM技术分析了自动驾驶系统路况识别检测原理,然后从训练模块和分类识别模块设计了系统模型和系统功能,最后采用模块化的思想设计了自动驾驶系统硬件平台,并基于QT环境开发搭建了系统上位机,实现了基于嵌入式和机器学习的农用车辆自动驾驶系统。试验结果表明:系统能够在常规作业中正常进行自动驾驶功能,符合设计要求,证明了系统的可行性、稳定性和有效性。
It first analyzes the principle of road condition identification detection in automatic driving system from PCA technology and SVM technology,and then designs the system model and system function from the training module and the classification recognition module.Finally,it designed the hardware platform of the automatic driving system by the modular idea,and the system is built on the basis of the QT environment development.It realized the automatic driving system for agricultural vehicles based on embedded and machine learning.The experimental results show that the system can carry on the automatic driving function in the normal operation,meet the design requirements,and prove the feasibility,stability and effectiveness of the system.
作者
梁硕
Liang Shuo(Henan Polytechnic Institute,Nanyang 473000,China)
出处
《农机化研究》
北大核心
2020年第2期256-260,共5页
Journal of Agricultural Mechanization Research
基金
河南省自然科学基金项目(2017GZC163)
