Taojie Yu
Papers
2
Total Citations
26
H-Index
2
About
Taojie Yu is a researcher at the forefront of agricultural robotics and intelligent automation, with a focus on overcoming real-world challenges in precision agriculture. His work centers on two critical areas: automated crop detection and robotic navigation in GNSS-denied environments. Yu’s major contribution includes the development of a novel algorithm for tea bud detection and 3D pose estimation using a depth camera, integrating an improved YOLOv5 model with an optimal pose-vertices search method. This innovation directly addresses a key bottleneck in tea picking automation, enabling robots to accurately locate and orient delicate buds in complex field conditions. The work has garnered 17 citations since 2023, reflecting its immediate relevance. Additionally, Yu has advanced agricultural robot navigation by proposing a rapid development methodology for systems operating without GPS, a vital capability for greenhouses and dense canopies. His research bridges computer vision, deep learning, and robotics, offering practical solutions for labor-intensive harvesting tasks. With a growing citation record and a focus on deployable technology, Yu is establishing himself as a promising contributor to smart farming and autonomous agriculture.
Research Focus
Key Achievements
Top Papers
- 1
- 2