Papers
14
Total Citations
376
H-Index
8
About
Yier Wu is a robotics researcher whose work centers on the calibration, accuracy improvement, and stiffness modeling of industrial robotic manipulators. His most significant contributions lie in developing advanced geometric and elastostatic calibration methodologies that enhance the precision of robots used in demanding applications such as large-scale composite material machining. His most cited work, "Geometric calibration of industrial robots using enhanced partial pose measurements and design of experiments" (2015, 189 citations), established him as a leading voice in robot calibration, demonstrating how partial pose measurements — which forgo end-effector orientation data — can still yield highly efficient identification procedures. Across multiple influential papers from 2012 to 2014, Wu systematically addressed the challenge of optimal measurement configuration selection, proposing novel optimality criteria and experimental design strategies that maximize calibration efficiency while minimizing resource demands. His stiffness modeling research further contributed to compensating elastic deflections during robot-based milling operations. More recently, Wu expanded his scope into soft robotics and adaptive grasping, exploring sensor-based reflex mechanisms for handling objects with uncertain positioning. With a body of work spanning rigorous mathematical modeling to practical manufacturing applications, Wu's research has meaningfully advanced the reliability and precision of modern industrial robots.
Research Focus
Key Achievements
Top Papers
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- 4Stiffness Modeling of Robotic Manipulator with Gravity Compensator24 citations · 2013
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