Wee Kin Teo
Papers
4
Total Citations
103
H-Index
4
About
Wee Kin Teo is a robotics and manufacturing researcher whose work sits at the compelling intersection of human skill capture and intelligent automation. His primary research focus centers on robotic surface finishing — specifically, solving one of manufacturing's most persistent challenges: translating the nuanced, experience-driven expertise of skilled human operators into programmable robot behavior. Teo's most significant contribution is his development of methodologies for capturing "tacit knowledge" — the instinctive, often unconscious techniques that expert grinders and polishers employ — and encoding this knowledge into robotic systems. Using instrumented, sensorized tools, his work systematically captures key process variables including contact force, tool path, feed rate, and tool orientation during human demonstration, then translates these parameters into functional robot programs. His 2015 paper on conformance grinding of complex shapes has garnered 51 citations, establishing it as a meaningful reference in the field, with subsequent work extending these principles to belt grinding and tool-orientation programming accumulating further recognition. For students exploring robotic programming, human-robot knowledge transfer, or advanced manufacturing automation, Teo's research offers a practical and elegant framework for preserving skilled human craftsmanship while achieving the consistency and scalability that industrial robotics demands.
Research Focus
Key Achievements
Top Papers
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