Shuhe Zheng
Papers
3
Total Citations
41
H-Index
2
About
Shuhe Zheng is a leading researcher in agricultural robotics, with a focused expertise in automated tomato harvesting systems. His work bridges computer vision and mechanical engineering to address critical challenges in fruit recognition, localization, and robotic manipulation. Zheng's most impactful contribution is the development of an improved YOLOv5n-seg model integrated with binocular stereo vision for tomato recognition and localization, a method that significantly reduces neural network complexity while enhancing accuracy—a key advancement for real-time harvesting applications (28 citations). He has also conducted foundational studies on the mechanical properties of tomatoes to inform end-effector design (12 citations), and most recently, characterized tomato pedicel physical properties to optimize fruit-pedicel separation mechanisms (2024). By systematically analyzing the physical and mechanical traits of tomatoes and their pedicels, Zheng provides essential data for designing more effective, damage-minimizing harvesting robots. His work is pivotal for advancing precision agriculture, offering scalable solutions that reduce computational overhead while improving robotic dexterity and reliability in field operations.
Research Focus
Key Achievements
Top Papers
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