Zhang Xiao-hui
Papers
5
Total Citations
44
H-Index
4
About
Zhang Xiao-hui is a leading researcher in assistive robotics, specializing in the development of intelligent lower-limb exoskeletons and exosuits that restore mobility to individuals with age-related or injury-induced impairments. Her work sits at the intersection of wearable robotics, control theory, and machine learning, with a core focus on making human-robot interaction seamless and intuitive. Her most cited paper (22 citations) introduces a machine-learning-driven controller that enhances the robustness of gait assistance in a hip exosuit, addressing the critical challenge of synchronizing robotic aid with voluntary human motion. She further demonstrated the practical impact of her designs with the LM-Ease exosuit, which improves the efficiency of sitting, standing, and walking. Zhang has also pioneered real-time locomotion mode recognition using only inertial measurement units, enabling exoskeletons to predict and smoothly transition between walking, stair climbing, and other activities. Her recent work integrates geometric modeling and computer vision for context-aware control, allowing exosuits to adapt assistance based on the user’s visual environment. With a career spanning from early sensor design to cutting-edge AI-driven control, Zhang is at the forefront of creating wearable robots that are not only powerful but perceptive and responsive to human intent.
Research Focus
Key Achievements
Top Papers
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- 5Design of new-style six-dimension force sensor system for robot finger3 citations · 2003