Ying-Kuan Tsai

National Taiwan University, Northwestern University

Papers

Total Citations

H-Index

About

Ying-Kuan Tsai is a robotics and intelligent manufacturing researcher whose work centers on uncertainty analysis in robot manipulation, mechanical system dynamics, and emerging Industry 4.0 technologies. His research addresses a critical challenge in robotic engineering: understanding and mitigating the sources of inaccuracy in robot manipulators, moving beyond conventional calibration approaches to investigate the root causes of operational error. In his most influential work, Tsai developed methods for identifying joint clearance through robot manipulation, recognizing that mechanical components such as gear transmission systems and joints are primary contributors to nongeometric uncertainty. His 2018 study extended this analysis to both serial and parallel robot manipulators, offering integrated uncertainty models suited for practical industrial applications. Together, these papers have accumulated over a dozen citations, establishing Tsai as a contributor to precision robotics research. More recently, Tsai has expanded his focus toward digital twin technology, proposing a real-time VR-enabled framework for multi-user interaction in Industry 4.0 environments. This work reflects his evolving interest in bridging physical robotic systems with intelligent virtual representations, supporting advanced monitoring and operational optimization in modern manufacturing contexts.