Papers
7
Total Citations
123
H-Index
4
About
Jong-Kyu Oh is a leading researcher in industrial robotics and machine vision, whose work has fundamentally advanced automated bin-picking and 3D measurement systems. His primary research areas include stereo vision, structured light sensing, and 3D pose estimation for industrial robots. Oh’s most impactful contribution is his pioneering work on stereo vision-based bin-picking automation, detailed in his 2012 paper (60 citations), which solved the critical challenge of enabling robots to recognize and grasp randomly oriented parts from bins without complete prior object knowledge. He further developed structured light-based bin-picking systems using primitive models (21 and 19 citations), significantly improving factory automation flexibility. His earlier development of a stereo vision system for industrial robots (17 citations) laid the groundwork for these advances, allowing robots to perceive their environment like human vision. Oh also introduced innovative methods for determining 3D poses of large objects using virtual plane algorithms and multi-line laser sensors, expanding measurement capabilities for complex industrial parts. With a cumulative impact of over 120 citations, his research remains essential for engineers designing robust, vision-guided robotic systems for real-world manufacturing.
Research Focus
Key Achievements
Top Papers
- 1Stereo vision based automation for a bin-picking solution60 citations · 2012
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- 4Development of a stereo vision system for industrial robots17 citations · 2007
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