Papers

4

Total Citations

54

H-Index

4

About

Paul Lin’s research career bridges the foundational mechanics of robotics with cutting-edge assistive artificial intelligence. His early work focused on improving robotic precision and control, notably through the application of the Taguchi method for kinematic tolerance specification—a contribution that remains his most cited work (34 citations). He also developed innovative methods for on-line calculation and compensation of static deflection in robot end-effectors, addressing critical limitations in lightweight robotic arms. In the 1980s, Lin pioneered a combined position and force sensor for robotic grippers, enhancing a robot’s ability to perceive object pose and applied load. More recently, his research has taken a transformative turn toward human-centered AI. His 2020 work on the “Robot Eye” system uses a deep attention network and a ZED stereo camera to detect and recognize objects, guiding blind individuals through outdoor environments. This project tackles unresolved challenges in computer vision while directly improving quality of life. With a career spanning from precision mechanics to socially impactful AI, Lin’s work demonstrates a sustained commitment to making robots more accurate, perceptive, and helpful to people.

Research Focus

Key Achievements

4
H-Index
4
Papers
54
Total Citations
14
Avg Citations/Paper
🏆 Most Cited Paper
Tolerance specification of robot kinematic parameters using an experimental design technique—the Taguchi method
34 citations · 1993
📈 Most Prolific Year: 1993 (1 Papers)
🤝 Key Collaborators: 9
🏛 Institutions: Cleveland State University, National Central University

Top Papers

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Key Collaborators

Contact & Links

Available for collaboration
Content generated · 13 days ago