Papers
11
Total Citations
242
H-Index
9
About
Xueyan Xing is a robotics researcher whose work sits at the intersection of human-robot interaction, adaptive control, and intelligent learning systems. With a growing body of highly cited publications, Xing has established herself as a significant contributor to the field of physical human-robot interaction (pHRI), where robots must safely and effectively collaborate with human users in dynamic, uncertain environments. Her most influential contributions center on impedance learning and iterative learning control (ILC), exploring how robots can intelligently adapt to human intent and environmental conditions. Her 2023 paper on impedance learning for human-guided robots has already garnered 63 citations, while her comprehensive 2022 review on interaction control through intent detection — with 54 citations — has become a valuable reference for researchers entering the field. Xing's work spans rehabilitation robotics, robotic exoskeletons, and collaborative manipulation, consistently addressing real-world challenges such as motion uncertainty, prescribed force delivery, and smooth authority-sharing between humans and machines. Her development of spatial iterative learning control and fuzzy logic-based arbitration frameworks demonstrates both theoretical depth and practical innovation. Collectively accumulating over 240 citations across her published works, Xing is rapidly emerging as an authoritative voice in intelligent, human-centered robotics research.
Research Focus
Key Achievements
Top Papers
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- 2A review on interaction control for contact robots through intent detection54 citations · 2022
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