Yong‐Joo Kim
Papers
8
Total Citations
234
H-Index
5
About
Dr. Yong-Joo Kim is a leading researcher in agricultural robotics and precision farming, with a focus on machine vision and autonomous navigation for field robots. His work centers on developing real-time perception systems that enable agricultural machinery to interact intelligently with crops and environments. A key contribution is his stereo-vision-based method for crop height estimation, which has garnered 103 citations and provides a foundation for automated crop monitoring. He has also advanced path detection in orchards using patch-based CNNs (68 citations) and developed techniques for 2D pose estimation of tomato fruit-bearing systems to support robotic harvesting (36 citations). Beyond perception, Dr. Kim has engineered control systems for electric tractors, including a Kalman-filter-integrated predictive motor-speed controller for real-time axle-torque prediction. His research extends to navigation, where he has evaluated the Quasi-Zenith Satellite System for guiding robot combine harvesters, and to tillage boundary detection using deep learning on RGB imagery. With over 230 citations across his most-cited works, Dr. Kim’s contributions are pivotal to the next generation of autonomous agricultural systems, bridging computer vision, robotics, and precision agriculture.
Research Focus
Key Achievements
Top Papers
- 1Stereo-vision-based crop height estimation for agricultural robots103 citations · 2020
- 2Path detection for autonomous traveling in orchards using patch-based CNN68 citations · 2020
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- 4Crop Height Measurement System Based on 3D Image and Tilt Sensor Fusion10 citations · 2020
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