Papers
4
Total Citations
69
H-Index
3
About
Shilei Lyu is a leading researcher at the intersection of agricultural robotics, human-robot collaboration, and computer vision. His work focuses on developing intelligent robotic systems for precision agriculture, particularly for fruit picking and orchard management. Lyu’s major contributions include pioneering the use of Virtual Reality to study human-robot interaction during collaborative tasks, a 2019 paper that has garnered 30 citations and established a new methodology for evaluating operator psychophysiological responses. He has significantly advanced agricultural automation through innovative deep learning approaches, such as the improved DeepLabv3+ architecture for citrus tree canopy segmentation (21 citations) and litchi branch segmentation (16 citations), enabling robots to perform precise spraying and automated picking in complex orchard environments. His most recent work on a lightweight, redundant-degree-of-freedom fruit-picking robot arm (2025) addresses critical labor shortages in the fruit industry by designing cost-effective alternatives to traditional industrial arms. With a growing citation impact and a focus on practical, deployable solutions, Lyu’s research is shaping the future of smart agriculture and human-robot teamwork.
Research Focus
Key Achievements
Top Papers
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- 3Method for Segmentation of Litchi Branches Based on the Improved DeepLabv3+16 citations · 2022
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