Kuan-Lin Li

Papers

Total Citations

H-Index

About

Kuan-Lin Li is a robotics researcher whose work centers on the precision, calibration, and reliability of robot manipulators — systems that form the backbone of modern industrial automation. His research addresses a fundamental challenge in robotics: how to improve the accuracy of robotic manipulation when real-world uncertainties, such as joint clearance and geometric parameter errors, inevitably affect performance. Li's most influential contribution, "An optimization technique for identifying robot manipulator parameters under uncertainty" (2016, 19 citations), introduced a rigorous approach to enhancing manipulation accuracy by systematically identifying and compensating for parameter uncertainties. Building on this foundation, his 2017 work on joint clearance identification pushed beyond conventional calibration methods to investigate the root sources of operational error — a deeper and more diagnostic perspective on robot imprecision. His research on dual-arm robot calibration using closed-chain constraints further extended these ideas to more complex robotic configurations, offering practical tools for next-generation collaborative systems. Collectively, Li's publications reflect a coherent and applied research vision: making robots more accurate, reliable, and self-aware in dynamic environments. His work is particularly valuable for engineers and researchers working on industrial automation, robot calibration, and uncertainty quantification in mechanical systems.