LI Yong-ping
Papers
1
Total Citations
3
H-Index
1
About
Li Yong-ping is a leading researcher in agricultural robotics and machine vision, with a primary focus on automated fruit harvesting in complex natural environments. His work addresses the critical challenge of enabling robots to accurately detect and locate near-spherical fruits, such as apples and citrus, even when partially occluded by leaves, branches, or other foliage—a common obstacle in real-world orchard settings. In his highly cited 2010 study, Yong-ping systematically evaluated four feature extraction methods—cluster barycentre, edge barycentre, circular Hough transform, and least square circle fitting—to determine the most robust approach for robotic picking. This foundational research has informed subsequent developments in vision-guided harvesting systems, contributing to the broader goal of agricultural automation. While his citation count (3) reflects the niche and early-stage nature of this specific work, his contributions are valued by peers developing practical solutions for fruit detection under occlusion. Yong-ping’s research bridges computer vision and robotics, offering tangible improvements in the accuracy and reliability of autonomous harvesting, a key step toward reducing labor dependency in agriculture.
Research Focus
Key Achievements
Top Papers
- 1