摘要
随着农业现代化的不断推进,农机自动化与智能化水平的提升成为农业技术发展的关键方向。该文围绕农机导航系统中的核心技术,研究传感器融合技术与机电控制技术的协同作用,并通过分析农机作业环境下常用的多种传感器类型,探讨传感器信息融合的卡尔曼滤波和深度学习算法,以提高导航系统的定位精度与稳定性,分析其在导航定位中的优势与局限性,并对未来融合智能算法与高精度控制策略的发展方向进行展望,旨在为智能农机导航系统的研究与工程实践提供系统的技术参考与理论支持。
With the continuous advancement of agricultural modernisation,the improvement of automation and intelligence level of agricultural machinery has become a key direction for the development of agricultural technology.This article focuses on the core technology in the navigation system of agricultural machinery,studies the synergy between sensor fusion technology and electromechanical control technology,and analyses a variety of sensor types commonly used in the operating environment of agricultural machinery,explores the Kalman filter and deep learning algorithms of sensor information fusion,in order to improve the positioning accuracy and stability of the navigation system,and analyses the advantages and limitations of its advantages and limitations in navigation and positioning,and looks forward to the development direction of the future fusion of intelligent algorithms and It also analyses its advantages and limitations in navigation and positioning,and looks forward to the future development direction of fusion of intelligent algorithms and high-precision control strategies,aiming to provide systematic technical references and theoretical support for the research and engineering practice of intelligent agricultural machinery navigation systems.
作者
王宏
王芸
WANG Hong;WANG Yun(Xinjiang Institute of Engineering,Urumqi 830023,China)
出处
《农机使用与维修》
2025年第8期78-81,共4页
Agricultural Machinery Using & Maintenance
关键词
农机导航
综述
传感器融合
机电控制
卡尔曼滤波
智能农业
agricultural machinery navigation
overview
sensor fusion
electromechanical control
Kalman filter
smart agriculture
