Papers

5

Total Citations

55

H-Index

4

About

Yaoqiang Pan is a pioneering researcher at the intersection of agricultural robotics, computer vision, and autonomous systems. His work centers on developing intelligent robotic solutions for precision horticulture, with key contributions in perception, mapping, and real-time defect detection. Pan’s most impactful work, “A novel perception and semantic mapping method for robot autonomy in orchards” (2024, 38 citations), establishes foundational methods for robotic navigation and environmental understanding in complex agricultural settings. He achieved a major breakthrough with his “finger vision” concept, the first eye-in-finger configuration for fruit inspection, enabling real-time defect detection during robotic harvesting with 98% precision while using less than 20% of a Jetson Orin’s computational capacity. His Phenobot system introduces autodigital modeling for in-situ phenotyping, addressing the critical gap between laboratory and field-based plant analysis. Pan also developed context-aware navigation frameworks for ground robots and autonomous digital modeling systems for unknown environments, advancing the frontier of Digital Twinning in agriculture. His integrated approach—combining SLAM-based semantic mapping, real-time visual inspection, and autonomous exploration—positions him as a leading innovator in bringing practical, intelligent robotics to sustainable agriculture.

Research Focus

Key Achievements

4
H-Index
5
Papers
55
Total Citations
11
Avg Citations/Paper
🏆 Most Cited Paper
A novel perception and semantic mapping method for robot autonomy in orchards
38 citations · 2024
📈 Most Prolific Year: 2024 (3 Papers)
🤝 Key Collaborators: 19
🏛 Institutions: South China Agricultural University, Monash University

Top Papers

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Key Collaborators

Contact & Links

Available for collaboration
Content generated · 13 days ago