Papers
5
Total Citations
79
H-Index
4
About
Xuan Liu is a robotics and biomedical engineering researcher whose work bridges soft robotics, bio-inspired locomotion control, and human-machine interaction. Liu's most influential contribution lies in developing hybrid control architectures for soft snake robots, combining reinforcement learning with central pattern generator (CPG) frameworks to achieve adaptive, biologically inspired locomotion — work that has garnered over 38 citations across related publications. This research demonstrates a sophisticated understanding of how neural control strategies found in nature can be translated into effective algorithms for compliant robotic systems. Equally significant is Liu's work in human motion estimation, where novel methods for continuously predicting elbow joint movement and time-varying stiffness using surface electromyography (sEMG) signals have advanced the field of robotic exoskeleton control. With nearly 40 combined citations across these studies, this research addresses a critical challenge in prosthetics and assistive robotics: accurately interpreting human physiological intent in real time. More recently, Liu has explored variable stiffness mechanisms through granular jamming structures, expanding contributions into soft robot hardware design. Collectively, Liu's research reflects a cohesive vision for intelligent, adaptive robotic systems that work in harmony with human physiology and movement.
Research Focus
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