Papers
2
Total Citations
4
H-Index
2
About
Liang Xu is a robotics and control systems researcher whose work spans two critical domains: rehabilitation robotics and fault-tolerant manipulator control. In the area of human-robot interaction, Xu has developed innovative torque estimation methods for lower limb rehabilitation robots, combining strong tracking Kalman filtering with moving average techniques to accurately and responsively capture the interaction forces exerted by patients during therapeutic training — a technically demanding challenge with direct clinical implications. Complementing this, Xu's earlier work addressed the reliability of redundant robotic manipulators, proposing an improved genetic algorithm strategy to maintain task performance when individual joints experience sudden failures, a contribution relevant to both industrial automation and safety-critical robotic applications. While Xu's published portfolio currently reflects an emerging research profile — with each notable work accumulating 2 citations — the practical significance of these contributions lies in their direct applicability to assistive technology and robust robotic systems. Students and collaborators interested in rehabilitation engineering, motion control, or fault-tolerant robotics will find Xu's focused methodological approach and interdisciplinary sensibility a valuable foundation for ongoing and future research partnerships.
Research Focus
Key Achievements
Top Papers
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- 2