Papers
6
Total Citations
177
H-Index
5
About
Shanjun Li is a leading researcher at the intersection of agricultural robotics, deep learning, and soft robotics, with a focus on revolutionizing post-harvest fruit processing and orchard automation. His most impactful work centers on developing intelligent vision systems for citrus sorting, where he has pioneered the use of deep learning architectures—including CNN-LSTM networks and detection-tracking frameworks—to achieve fast, accurate, on-line defect identification. His 2021 paper on a deep learning-based vision system for citrus sorting has garnered 70 citations, while his 2023 work on non-destructive fruit firmness evaluation using a soft gripper and vision-based tactile sensing has already reached 53 citations, underscoring its significance. Beyond sorting, Li has contributed to soft actuator design with bio-inspired origamic pouch motors that achieve high contraction ratios, and to orchard automation through cable-driven target spray robots for hilly terrains. His early work on grasp planning for underactuated robot hands laid foundational strategies for fruit grasping. With a portfolio spanning from tactile sensing to robotic manipulation, Li’s research is driving the next generation of efficient, intelligent agricultural systems.
Research Focus
Key Achievements
Top Papers
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- 3A vision system based on CNN-LSTM for robotic citrus sorting23 citations · 2022
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