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Robust localization and tracking control of high-clearance robot system servicing high-throughput wheat phenotyping

文献类型： 外文期刊

作者： Hu, Qinghan 1 ; Fan, Zhengqiang 1 ; Zhang, Xihai 4 ; Sun, Na 3 ; Li, Xuefeng 6 ; Qiu, Quan 1 ;

作者机构： 1.Beijing Univ Agr, Coll Intelligent Sci & Engn, Beijing 102206, Peoples R China

2.Beijing Univ Chem Technol, Coll Informat Sci & Technol, Beijing 100029, Peoples R China

3.Beijing Acad Agr & Forestry Sci, Intelligent Equipment Res Ctr, Beijing 100097, Peoples R China

4.Northeast Agr Univ, Coll Elect & Informat, Harbin 150030, Peoples R China

5.Southwest Univ, Coll Engn & Technol, Chongqing 400715, Peoples R China

6.Tianjin Res Inst Construct Machinery, Tianjin 300000, Peoples R China

关键词： High-throughput wheat phenotyping; Phenotyping robot; High-clearance; Combined positioning; Trajectory tracking

期刊名称：COMPUTERS AND ELECTRONICS IN AGRICULTURE （ 影响因子：8.9； 五年影响因子：9.3 ）

ISSN： 0168-1699

年卷期： 2025 年 229 卷

页码：

收录情况： SCI

摘要： High-throughput phenotyping robots are transforming crop sample collection methods to enable the efficient acquisition of high-quality samples. Currently, large high-clearance robots stand out in high-throughput wheat phenotyping with advantages like high precision and close-range observation. However, research on large high- clearance robots remains limited, especially in autonomous localization and trajectory tracking. To overcome this limitation, a large high-clearance robot system is built for high-throughput wheat phenotyping in this paper. The chassis height of the high-clearance robot reaches 1.6 meters, accommodating the full growth cycle height of wheat. In particular, the system is optimized for localization and trajectory tracking infield environments. An adaptive Kalman filtering-based GNSS/INS combined positioning algorithm is proposed to handle poor GNSS signals in occluded environments. Additionally, a fuzzy PID control strategy is proposed to adaptively adjust the PID parameters, reducing deviations caused by environmental disturbances. Finally, a human-computer system is developed to enable remote control of the robot and display its status information. The field experimental results show that: the remote control system is verified to have high performance through 400 sets of experiments; the average angular velocity error of left and right hub motors is 0.08 rad/s; the average position deviation of the proposed adaptive Kalman filtering algorithm is 0.225 m, and the average heading deviation is 0.308 degrees ; the mean lateral deviation and heading deviation of trajectory tracking controller based fuzzy PID are 0.076 m and 1.746 degrees , respectively. According to the experimental results, the aforementioned high-clearance robot system can provide strong support for the precise observation and efficient analysis of wheat phenotypic data.

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