Papers
3
Total Citations
39
H-Index
3
About
Wengang Zheng is a leading researcher in agricultural robotics and intelligent automation, with a focus on solving critical labor shortages in modern farming. His work spans machine vision, robotic manipulation, and deep reinforcement learning for precision agriculture. Zheng’s most impactful contributions include a dynamic task planning framework for multi-arm apple-harvesting robots, integrating LSTM networks with Proximal Policy Optimization (PPO) to enable real-time coordination and adaptive picking strategies—a paper already garnering 16 citations shortly after publication. He also developed a machine vision-based detection method for leafy vegetable seedling transplanting, using the PV200 image processor to identify empty cells and unqualified seedlings, achieving 12 citations for its practical utility in automated nurseries. Additionally, his design of a scion cutting mechanism for cucurbit grafting robots addressed the critical challenge of seedling stem curvature, improving cutting precision and graft survival rates, with 11 citations. Zheng’s work directly bridges advanced AI algorithms with deployable agricultural machinery, offering scalable solutions for high-value crops like apples, cucumbers, and watermelons. His research is essential reading for engineers and agronomists developing next-generation autonomous farming systems.
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