Papers
2
Total Citations
29
H-Index
2
About
Shuyuan Xu is a researcher advancing the frontiers of human-robot interaction and assistive robotics, with a primary focus on lower limb exoskeleton systems and live-working robotic manipulators. Their work addresses critical challenges in making robotic systems more responsive and precise in real-world applications. Xu’s most notable contribution is a novel lower limb motion recognition method that integrates improved wavelet packet transforms with an unscented Kalman neural network, enabling more flexible and intuitive control of exoskeletons through surface electromyography (sEMG) signals. This work, published in 2020, has garnered 24 citations, reflecting its impact on the field of rehabilitation and assistive robotics. Additionally, Xu has developed a trajectory planning method for live-working robots that compensates for base sloshing on aerial platforms using feedforward control and quintic polynomial interpolation, achieving a 5-citation count. By tackling both motion intention recognition and precision control, Xu’s research directly enhances the safety and effectiveness of robots in human-centric environments, from medical exoskeletons to high-risk electrical maintenance tasks. Their work stands as a bridge between biological signals and mechanical action, promising more seamless human-robot collaboration.
Research Focus
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Top Papers
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