Papers

3

Total Citations

652

H-Index

3

About

Xiaoyan Lei is a leading researcher in agricultural robotics, specializing in computer vision and intelligent control systems for fruit harvesting. Her work focuses on solving the critical challenge of enabling robots to accurately detect and grasp apples in complex orchard environments. Lei’s most impactful contribution is the development of a real-time apple target detection method based on an improved YOLOv5 algorithm, which has garnered over 560 citations. This work addresses the difficult problem of distinguishing apples occluded by branches or other fruit, a key bottleneck for picking robot autonomy. She further advanced the field by designing a three-finger gripper and analyzing optimal picking patterns for robotic apple harvesting, as well as proposing a multi-feature, patch-based segmentation technique in the gray-centered RGB color space to overcome issues of halation and shadow on fruit surfaces. Her research directly bridges the gap between computer vision theory and practical agricultural automation, providing foundational algorithms for the next generation of intelligent harvesting systems.

Research Focus

Key Achievements

3
H-Index
3
Papers
652
Total Citations
217
Avg Citations/Paper
🏆 Most Cited Paper
A Real-Time Apple Targets Detection Method for Picking Robot Based on Improved YOLOv5
564 citations · 2021
📈 Most Prolific Year: 2021 (3 Papers)
🤝 Key Collaborators: 7
🏛 Institutions: Northwest A&F University, Institute of Soil and Water Conservation

Top Papers

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Key Collaborators

Contact & Links

Available for collaboration
Content generated · 12 days ago