Yunwen Xu
Papers
7
Total Citations
89
H-Index
4
About
Yunwen Xu is a robotics researcher whose work bridges control theory, visual servoing, and soft robotics. Their key research areas include iterative learning control, data-driven compensation, and hybrid rigid-soft robotic systems. Xu’s major contributions lie in developing robust control algorithms that address real-world uncertainties—for instance, their 2021 paper on iterative learning control with data-driven compensation (40 citations) tackles the conservatism of traditional robust designs by using system data to adaptively handle unknown time-varying uncertainty. In visual servoing, Xu proposed an eye-in-hand control method (27 citations) that leverages output-input data to mitigate parametric uncertainties, and an adaptive control algorithm for uncalibrated position-based visual servoing (5 citations) that avoids complex calibration. Notably, Xu’s 2023 work on a rigid-soft hybrid robot with visual servoing (8 citations) introduces a novel framework that combines the accuracy of rigid robots with the safe interaction of soft robots, achieving improved performance for tasks like touch screens and human-machine interaction. With over 90 total citations across their publications, Xu’s research is shaping the future of adaptive, data-driven robotic systems.
Research Focus
Key Achievements
Top Papers
- 1Iterative Learning Control With Data-Driven-Based Compensation40 citations · 2021
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- 7A Robust Model Reconstruction Algorithm For Elevator Shaft2 citations · 2023