Yulan Chang
Papers
1
Total Citations
12
H-Index
1
About
Yulan Chang is a researcher specializing in precision measurement and robotic vision, with a particular focus on high-accuracy industrial inspection systems. Her most cited work, "Research on high-precision hole measurement based on robot vision method" (2014), has garnered 12 citations and represents a significant contribution to the field of automated quality control. In this study, Chang developed a novel approach that integrates robotic vision with advanced image processing algorithms to achieve sub-millimeter accuracy in measuring hole dimensions—a critical requirement in aerospace, automotive, and precision manufacturing. Her method addresses key challenges in traditional measurement techniques, such as human error and limited repeatability, by leveraging robot-guided cameras and calibration models. This work has practical implications for enhancing production efficiency and product reliability. Chang’s research bridges the gap between theoretical computer vision and real-world industrial applications, demonstrating how robotic systems can be optimized for high-precision tasks. Her contributions continue to influence the development of smarter, more autonomous inspection systems in manufacturing environments.
Research Focus
Key Achievements
Top Papers
- 1Research on high-precision hole measurement based on robot vision method12 citations · 2014