Ying Chun Chen

Kunming University of Science and Technology

Papers

Total Citations

H-Index

About

Ying Chun Chen is a researcher in robotics and computer vision, with a primary focus on camera calibration techniques for robotic systems. His most cited work, "Monocular Camera Calibration Method for Robot System" (2015), introduces a practical approach to calibrating monocular cameras using a 2D plane circular array. The method employs Canny edge detection to extract elliptical edge coordinates, followed by ellipse fitting to determine precise center points—a foundational step for accurate spatial perception in robots. While his citation count remains modest, Chen’s contribution addresses a critical challenge in robotic vision: enabling machines to interpret their environment through reliable camera geometry. This work is particularly relevant for applications in autonomous navigation, object manipulation, and industrial automation, where precise calibration directly impacts system performance. Chen’s research underscores the importance of accessible, efficient calibration methods that bridge theoretical optics and real-world robotic implementation, offering a practical resource for engineers and researchers developing vision-guided systems.