我国智能农业拖拉机关键技术研究进展

doi:10.12398/j.issn.2096-7217.2022.02.002

摘要/Abstract

摘要： 智能化是拖拉机产品的发展方向，智能农业拖拉机已成为农业机械行业的研究热点。在参考智能农业装备研究的基础上，提出了智能农业拖拉机的定义，并阐述智能农业拖拉机的关键特点。分别就自动导航、自动换挡、操控系统、智能耕作系统等关键技术的研究进展进行分析，指出无人驾驶、联网云控制、精准控制、智能终端将是智能农业拖拉机的发展方向。智能农业拖拉机是智慧农业技术的关键载体，国内在智能拖拉机上的研究较多，但是在智能操控终端、远程联网控制、控制的精度与可靠性上与国外先进水平的差距仍然较大，国内拖拉机相关研发生产机构应加快关键技术的研究，寻求智能拖拉机发展的突破，助力高质高量农业机械化发展。

关键词: 智能农业装备, 拖拉机, 卫星定位, 自动驾驶, 精准控制

Abstract: Intellectualization is the orientation of tractors products. Intelligent agricultural tractors have become a research hotspot in agricultural machinery. Based on the research of intelligent agricultural equipment, this paper puts forward the definition of intelligent agricultural tractors and expounds the key characteristics of intelligent agricultural tractors. This paper analyzes the research progress of key technologies such as automatic navigation, automatic shift, control system and intelligent farming system, and points out that driverless technology, networked cloud control, precision control and intelligent terminal will be the orientation of intelligent agricultural tractors. Also, intelligent agricultural tractors are the key carrier of intelligent agricultural technology. There are many researches on intelligent tractors in China, but the research level of intelligent control terminal, remote networked control, control accuracy and reliability of intelligent tractors in China lags far behind that in foreign countries. Domestic tractors manufacturers should speed up the research on key technologies, seek breakthroughs in the development of intelligent tractors, and promote the development of highquality and efficient agricultural mechanization.

Key words: intelligent agricultural equipment, tractor, satellite positioning；automatic driving, precise control

中图分类号:

S232.3:S24

白学峰, 常江雪, 滕兆丽, 鲁植雄. 我国智能农业拖拉机关键技术研究进展[J]. 智能化农业装备学报（中英文）, 2022, 3(2): 10-21.

Bai Xuefeng, Chang Jiangxue, Teng Zhaoli, Lu Zhixiong. Research progress on key technologies of intelligent agricultural tractors in China[J]. Journal of Intelligent Agricultural Mechanization, 2022, 3(2): 10-21.

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