Design and Development of a Vision-Guided Automated Chinese Yam Seedling Planter

Chinese yam planting requires horizontal placement, consistent apical–basal orientation, controlled spacing, and low-damage handling of slender seed segments. This study developed and field-evaluated an integrated vision-guided Chinese yam planter combining furrow opening, feeding, visual inspection and rejection, orientation adjustment, buffered discharge, spacing regulation, furrow tracking, seed placement, and soil covering. Conventional image processing extracted seed-segment length and end orientation, an EfficientNet-B0–kNN one-class method supported auxiliary visual-anomaly screening, and a YOLO11s-seg model with PID control-enabled furrow tracking. Field tests and a two-factor experiment were conducted under sandy-soil conditions. The prototype achieved 22 seedlings min−1, a spacing coefficient of variation of 8.4%, a miss-seeding rate of 4.5 ± 1.3%, an orientation accuracy of 99%, and a path-tracking RMSE of 2.30 ± 0.18 cm; forward velocity was the dominant factor affecting spacing uniformity. The screening module achieved a 98.6% interception rate on marker-simulated anomalies under controlled imaging conditions, while recognition of natural defects remains unvalidated. The system can reduce reliance on skilled labor, and its modular structure and quantified performance provide practical references for users and equipment manufacturers.