Zhenbo Xin
Papers
4
Total Citations
36
H-Index
4
About
Zhenbo Xin is a pioneering researcher in agricultural robotics, specializing in the automation of specialty crop harvesting. His work focuses on developing intelligent robotic systems for high-value crops like white asparagus and tomatoes, addressing the unique challenges of selective harvesting in complex field environments. Xin’s major contributions include the creation of lightweight deep learning models such as HGCA-YOLO, which enables real-time recognition of invisible spears for white asparagus harvesting, and the design of novel hybrid end-effectors that combine bending, twisting, and pulling motions for delicate tomato picking. He has also advanced multi-robot coordination with parallel dual-arm control methods that integrate moving, looking, and harvesting actions, as well as subsoil 3D cutting-point location techniques for precise green asparagus harvesting. With his most-cited paper garnering 14 citations and several recent works accumulating over 8 citations each, Xin’s research is gaining rapid recognition. His innovative approaches to robotic manipulation and perception are paving the way for practical, efficient automation in agriculture, making him a key figure in the future of smart farming.
Research Focus
Key Achievements
Top Papers
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