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Mengke Zhang, Xiaoguang Li, Ling Wang, Liujian Jin and Shubo Wang
The application of intelligent mobile robots in agriculture has emerged as a new research frontier, with the integration of autonomous navigation technology and intelligent agricultural robots being the key to the widespread adoption of smart agricultura...
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Hui Liu, Kun Li, Luyao Ma and Zhijun Meng
Headland boundary identification and ranging are the key supporting technologies for the automatic driving of intelligent agricultural machinery, and they are also the basis for controlling operational behaviors such as autonomous turning and machine lif...
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Haoling Ren, Jiangdong Wu, Tianliang Lin, Yu Yao and Chang Liu
Intelligent agricultural machinery refers to machinery that can independently complete tasks in the field, which has great significance for the transformation of agricultural modernization. However, most of the existing research on intelligent agricultur...
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Lijun Xu, Qinhan Chen, Linlin Wang and Lijian Yao
This paper proposes a path-tracking method for agricultural vehicles based on the 4WIS-4WID structure and fuzzy control to improve the operation performance of agricultural machinery in the greenhouse. The influential model of two critical parameters, a ...
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Wenjie Li, Wen Dong, Xin Zhang and Jinzhong Zhang
Remote sensing, the Internet, the Internet of Things (IoT), artificial intelligence, and other technologies have become the core elements of modern agriculture and smart farming. Agricultural production and management modes guided by data and services ha...
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Tengxiang Yang, Chengqian Jin, Youliang Ni, Zhen Liu and Man Chen
Aiming at the demand by unmanned farms for unmanned operation in the entire process of field management, an unmanned plant protection robot for field management was developed based on a platform comprising a traditional high-clearance spray rod sprayer, ...
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Zhao Xue, Jun Fu, Qiankun Fu, Xiaokang Li and Zhi Chen
Green forage maize harvesters face challenges such as high soil humidity and soft soil in the field, mismatched working parameters, and poor reliability and adaptability. These challenges often result in header blockage, significant harvest loss, and inc...
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Cheng?en Li, Yunchao Tang, Xiangjun Zou, Po Zhang, Junqiang Lin, Guoping Lian and Yaoqiang Pan
Agricultural machinery intelligence is the inevitable direction of agricultural machinery design, and the systems in these designs are important tools. In this paper, to address the problem of low processing power of traditional agricultural machinery de...
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Yonglian Han, Min Shao, Yunzhi Wu and Xiaoming Zhang
The advancement of society and technology has promoted the development of modern agriculture. It has become a trend to replace traditional manpower with intelligent agricultural machinery that operates independently. As the core technology of intelligent...
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Jiajia Sheng, Youqiang Sun, He Huang, Wenyu Xu, Haotian Pei, Wei Zhang and Xiaowei Wu
Cropland extraction has great significance in crop area statistics, intelligent farm machinery operations, agricultural yield estimates, and so on. Semantic segmentation is widely applied to remote sensing image cropland extraction. Traditional semantic ...
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