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Design and Experiment of Autonomous Shield-Cutting End-Effector for Dual-Zone Maize Field Weeding

Author

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  • Yunxiang Li

    (Beijing Institute of Technology, Beijing 100081, China
    The State Key Laboratory of Multimodal Artificial Intelligence Systems, Institute of Automation, Chinese Academy of Sciences, Beijing 100190, China)

  • Yinsong Qu

    (Beijing Institute of Technology, Beijing 100081, China
    The State Key Laboratory of Multimodal Artificial Intelligence Systems, Institute of Automation, Chinese Academy of Sciences, Beijing 100190, China)

  • Yuan Fang

    (The State Key Laboratory of Multimodal Artificial Intelligence Systems, Institute of Automation, Chinese Academy of Sciences, Beijing 100190, China)

  • Jie Yang

    (Beijing Institute of Technology, Beijing 100081, China)

  • Yanfeng Lu

    (The State Key Laboratory of Multimodal Artificial Intelligence Systems, Institute of Automation, Chinese Academy of Sciences, Beijing 100190, China)

Abstract

This study presented an autonomous shield-cutting end-effector for maize surrounding weeding (SEMSW), addressing the challenges of the low weed removal rate (WRR) and high seedling damage rate (SDR) in northern China’s 3–5 leaf stage maize. The SEMSW integrated seedling positioning, robotic arm control, and precision weeding functionalities: a seedling positioning sensor identified maize seedlings and weeds, guiding XYZ translational motions to align the robotic arm. The seedling-shielding anti-cutting mechanism (SAM) enclosed crop stems, while the contour-adaptive weeding mechanism (CWM) activated two-stage retractable blades (TRWBs) for inter/intra-row weeding operations. The following key design parameters were determined: 150 mm inner diameter for the seedling-shielding disc; 30 mm minimum inscribed-circle for retractable clamping units (RCUs); 40 mm ground clearance for SAM; 170 mm shielding height; and 100 mm minimum inscribed-circle diameter for the TRWB. Mathematical optimization defined the shape-following weeding cam (SWC) contour and TRWB dimensional chain. Kinematic/dynamic models were introduced alongside an adaptive sliding mode controller, ensuring lateral translation error convergence. A YOLOv8 model achieved 0.951 precision, 0.95 mAP50, and 0.819 mAP50-95, striking a balance between detection accuracy and localization precision. Field trials of the prototype showed 88.3% WRR and 2.2% SDR, meeting northern China’s agronomic standards.

Suggested Citation

  • Yunxiang Li & Yinsong Qu & Yuan Fang & Jie Yang & Yanfeng Lu, 2025. "Design and Experiment of Autonomous Shield-Cutting End-Effector for Dual-Zone Maize Field Weeding," Agriculture, MDPI, vol. 15(14), pages 1-22, July.
  • Handle: RePEc:gam:jagris:v:15:y:2025:i:14:p:1549-:d:1705060
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