https://doi.org/10.4081/jae.2023.1539

An efficient headland-turning navigation system for a safflower picking robot

Vol. 54 No. 3 (2023)
Published: 11 October 2023
Safflower picking robot, headland-turning navigation, trajectory planning and tracking
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Authors

Guomin Gao
College of Mechanical and Electrical Engineering, Xinjiang Agricultural University, Urumqi, China.
Hui Guo
gh97026@126.com
College of Mechanical and Electrical Engineering, Xinjiang Agricultural University, Urumqi, China.
Jing Zhang
College of Mechanical and Electrical Engineering, Xinjiang Agricultural University, Urumqi; Department of Biosystems Engineering, Zhejiang University, Hangzhou, China.
Zhenguo Zhang
College of Mechanical and Electrical Engineering, Xinjiang Agricultural University, Urumqi, China.
Tianlun Wu
College of Mechanical and Electrical Engineering, Xinjiang Agricultural University, Urumqi, China.
Hao Lu
College of Mechanical and Electrical Engineering, Xinjiang Agricultural University, Urumqi, China.
Zhaoxin Qiu
College of Mechanical and Electrical Engineering, Xinjiang Agricultural University, Urumqi, China.
Haiyang Chen
College of Mechanical and Electrical Engineering, Xinjiang Agricultural University, Urumqi, China.
Zhen Lingxuan
College of Electronic and Information Engineering, Southwest University, Chongqing, China.

This study proposes a navigation system for the headland autonomous turning of a safflower picking robot. The proposed system includes binocular cameras, differential satellites, and inertial sensors. The method of extracting the headland boundary line combining the hue, saturation, and value-fixed threshold segmentation method and random sample consensus algorithm and planning the headland-turning trajectory of a robot based on the multiorder Bezier curve are used as control methods. In addition, a headland-turning tracking model of a safflower picking robot is designed, and a path-tracking control algorithm is developed. A field test verifies the performance of the designed headland-turning navigation system. The test results show that the accuracy of the judgment result regarding the existence of a headland is higher than 96%. In headland boundary detection, the angle deviation is less than 1.5˚, and the depth value error is less than 50 mm. The headland-turning path tracking test result shows that at a turning speed of 0.5 km/h, the average lateral deviation is 37 mm, and the turning time is 24.2 seconds. Compared to the 1 km/h, the turning speed of 0.5 km/h provides a better trajectory tracking effect, but the turning time is longer. The test results verify that this navigation system can accurately extract the headland boundary line and can successfully realise the headland-turning path tracking of a safflower picking robot. The results presented in this study can provide a useful reference for the autonomous navigation of a field robot.

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How to Cite

Gao, G., Guo, H., Zhang, J., Zhang, Z. ., Wu, T. ., Lu, H. ., Qiu, Z. ., Chen, H. . and Lingxuan, Z. . (2023) “An efficient headland-turning navigation system for a safflower picking robot”, Journal of Agricultural Engineering, 54(3). doi: 10.4081/jae.2023.1539.
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