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Path Planning and Control System Design of an Unmanned Weeding Robot

Author

Listed:
  • Tengxiang Yang

    (Nanjing Institute of Agricultural Mechanization, Ministry of Agriculture and Rural Affairs, Nanjing 210014, China)

  • Chengqian Jin

    (Nanjing Institute of Agricultural Mechanization, Ministry of Agriculture and Rural Affairs, Nanjing 210014, China)

  • Youliang Ni

    (Nanjing Institute of Agricultural Mechanization, Ministry of Agriculture and Rural Affairs, Nanjing 210014, China)

  • Zhen Liu

    (Nanjing Institute of Agricultural Mechanization, Ministry of Agriculture and Rural Affairs, Nanjing 210014, China)

  • Man Chen

    (Nanjing Institute of Agricultural Mechanization, Ministry of Agriculture and Rural Affairs, Nanjing 210014, China)

Abstract

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, integrated unmanned driving technology, image recognition technology, intelligent control technology, and precision operation technology. According to the agricultural machinery operation mode, agricultural machinery path planning, linear path tracking, and header path tracking algorithms were developed. Based on the overall structure and working principle of the chassis, the robot control system, steering control system, and operation control system were set. Based on the YOLOv5 image recognition algorithm, the crop–weed recognition model was developed. After 6000 rounds of training, the accuracy, recall, and mean average precision of the model were 87.7%, 84.5%, and 79.3%, respectively. Finally, a field experiment was carried out with the unmanned plant protection robot equipped with a complete system. Results show that the average lateral error of the robot is 0.036 m, the maximum lateral error is 0.2 m, the average root mean square error is 0.053 m, the average velocity error is 0.034 m/s, and the average root mean square error of velocity is 0.045 m/s when the robot works in a straight line. In weeding operations, the area ratio of weedy zones to field is 25%, which saves 75% of the herbicide compared to that dispensed in full spraying mode. The unmanned plant protection robot designed in this study effectively achieves machinery’s autonomous operation, providing valuable insights for research in unmanned farming and autonomous agricultural machinery.

Suggested Citation

  • Tengxiang Yang & Chengqian Jin & Youliang Ni & Zhen Liu & Man Chen, 2023. "Path Planning and Control System Design of an Unmanned Weeding Robot," Agriculture, MDPI, vol. 13(10), pages 1-15, October.
  • Handle: RePEc:gam:jagris:v:13:y:2023:i:10:p:2001-:d:1260162
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    References listed on IDEAS

    as
    1. Tiago Domingues & Tomás Brandão & João C. Ferreira, 2022. "Machine Learning for Detection and Prediction of Crop Diseases and Pests: A Comprehensive Survey," Agriculture, MDPI, vol. 12(9), pages 1-23, September.
    2. Ivo Vatavuk & Goran Vasiljević & Zdenko Kovačić, 2022. "Task Space Model Predictive Control for Vineyard Spraying with a Mobile Manipulator," Agriculture, MDPI, vol. 12(3), pages 1-20, March.
    Full references (including those not matched with items on IDEAS)

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    Cited by:

    1. Weidong Jia & Kaile Tai & Xiaowen Wang & Xiang Dong & Mingxiong Ou, 2024. "Design and Simulation of Intra-Row Obstacle Avoidance Shovel-Type Weeding Machine in Orchard," Agriculture, MDPI, vol. 14(7), pages 1-22, July.

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