Design and experiment of automatic docking system for liquid pesticide replenishment tube of field sprayer

文献类型： 外文期刊

第一作者： Gao, Yuanyuan

作者： Gao, Yuanyuan;Feng, Kangyao;Wei, Xinhua;Han, Xin;Hu, Yongyue;Lu, Shengwei;Chen, Liping;Gao, Yuanyuan;Wei, Xinhua;Liu, Jingkai;Chen, Liping

作者机构：

关键词： Field sprayer; Autonomous operation; Liquid pesticide replenishment; Robotic arm; CAN bus; Visual servo; Positioning and docking

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 235 卷

页码：

收录情况： SCI

摘要： Field sprayers are constrained by the capacity of their pesticide tanks. During continuous operation, the operation process needs to be frequently interrupted for station-based replenishment or manual-assisted replenishment, significantly reducing the operational area and efficiency. To address the low efficiency of artificial replenishment of liquid pesticide and insufficient automation of liquid medicine replenishment in large-scale farms, this study develops an automatic docking system for liquid pesticide replenishment tube (LPRT) targeting the field sprayer. The kinematic workspace analysis and robotic structure design were carried out by establishing the kinematic model of the docking robotic arm (DRA). Based on the requirements of replenishment operations, the structure of the pesticide tank filling opening is improved, and a YOLOv5s-based recognition and positioning method for the pesticide tank filling opening is proposed. Additionally, a flexible guidance and automatic retraction mechanism for the LPRT was designed, along with a visual servo-based precise docking algorithm. The communication protocol between each module based on the CAN bus is formulated, and the automatic replenishment monitoring system for the field sprayer is developed. The system's performance is tested through actual experiments. The visual recognition tests showed that the improved algorithm achieved a recognition confidence level exceeding 0.95 under different lighting conditions, which can adapt to the complex scene requirements of field operations. The performance test results of the pesticide tank filling opening recognition show that the pesticide tank filling opening recognition algorithm has good applicability and stability within the replenishment operation range, the best effect is achieved when the recognition distance is 30-60 cm and the recognition angle is above 30 degrees. Further field docking tests revealed that the average operation time of the DRA is 35.64 s, the position repeated positioning accuracy is 4.12 cm, and the error ratio is 8 %, meeting the requirements for automated replenishment between the field sprayer and the replenishment vehicle. This study provides a practical solution and technical reference for improving the automation of pesticide replenishment in field sprayers, thereby enhancing the level of unmanned agricultural applications.

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