Papers
7
Total Citations
213
H-Index
5
About
Yatao Li is a pioneering researcher at the intersection of agricultural robotics, computer vision, and precision automation, with a focused expertise in intelligent tea harvesting systems. His work addresses one of modern agriculture's most pressing challenges: automating the labor-intensive harvesting of high-value tea crops in complex, unstructured field environments. Li's most influential contribution, "In-field tea shoot detection and 3D localization using an RGB-D camera" (2021, 94 citations), established a foundational framework for spatially aware crop detection, enabling robotic systems to precisely locate delicate tea shoots. Building on this, he developed and field-validated a complete robotic harvesting system (2023, 60 citations), demonstrating real-world viability of autonomous tea plucking. His compressed YOLOv3-SPP detection model further advanced the field by delivering high-accuracy, real-time performance on resource-constrained hardware (2022, 28 citations). More recently, Li has expanded into multi-species, multi-season detection models and binocular stereo vision localization, while also contributing novel kinetostatic modeling for soft robotic grippers. His research on greenhouse seedling transplantation robots underscores a broader commitment to intelligent agricultural automation. With nearly 200 cumulative citations, Li's work is rapidly shaping the future of precision horticulture robotics.
Research Focus
Key Achievements
Top Papers
- 1In-field tea shoot detection and 3D localization using an RGB-D camera94 citations · 2021
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- 6DMT: A model detecting multispecies of tea buds in multi-seasons3 citations · 2024
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