Cheng-Yun Yang

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About

Cheng-Yun Yang is a researcher specializing in industrial robotics and intelligent manufacturing, with a particular focus on precision assembly technologies. Their key research areas include 2D point cloud matching, shape recognition algorithms, and robotic automation for complex assembly tasks. Yang’s major contribution lies in developing a fast shaft hole assembly method that integrates image recognition with robotic control, addressing critical challenges in part variety and manual assembly limitations. Their work on "Research on Fast Shaft Hole Assembly Technology Based on 2D Point Cloud Matching Shape Recognition Method by Industrial Robot" (2023) has garnered 2 citations, demonstrating early impact in the field. This research is notable for its practical application in improving assembly efficiency and accuracy, which is vital for modern manufacturing. Yang’s innovative approach to combining computer vision with robotics positions them as a promising contributor to automation technology, offering solutions that enhance equipment performance and reduce human error in assembly processes.