Papers
8
Total Citations
114
H-Index
6
About
Yung-Jung Chang is a robotics researcher whose work centers on hand-eye calibration, visual servoing, and real-time machine vision for robotic manipulation. His major contributions lie in developing novel calibration techniques that simultaneously determine camera intrinsic parameters and hand-eye-workspace transformations, significantly reducing positioning errors in automated systems. His 2012 paper on automatic calibration using a hand-mounted line laser has garnered 37 citations, demonstrating its impact on the field. Chang has also advanced robotic ball-catching and throwing systems with visual feedback, integrating stereo vision and embedded processors for real-time tracking. His work on FPGA-based template matching for visual inspection, with 17 citations, addresses the computational bottlenecks of normalized cross-correlation algorithms. Additionally, his kinematic calibration method using a single laser pointer simplifies robot calibration procedures. Chang's research has practical applications in industrial automation, where precise calibration and real-time visual feedback are critical. His work on omni-directional wheeled robot control using optical flow sensors further showcases his versatility in mobile robotics. Through these contributions, Chang has established himself as a researcher dedicated to improving the accuracy, speed, and reliability of vision-guided robotic systems.
Research Focus
Key Achievements
Top Papers
- 1
- 2A ball-throwing robot with visual feedback19 citations · 2010
- 3
- 4
- 5Kinematic calibration of manipulator using single laser pointer8 citations · 2012
- 6
- 7A robotic ball catcher with embedded visual servo processor6 citations · 2010
- 8