Papers
2
Total Citations
13
H-Index
2
About
Yawen Chen is a researcher at the forefront of human-robot interaction and exoskeletal robotics, with a focus on bio-inspired control systems and physical human-robot collaboration. Her work addresses critical challenges in making robotic systems safer, more adaptive, and responsive to human motion. Chen’s most cited paper, "Bio-Inspired Real-Time Prediction of Human Locomotion for Exoskeletal Robot Control" (2017, 9 citations), tackles the fundamental problem of delay in inertial measurement unit-based motion capture, proposing a bio-inspired approach to predict human locomotion in real time for improved exoskeleton control. This contribution is vital for advancing assistive and rehabilitation robotics. In her notable 2020 work, "Variable Stiffness Control with Strict Frequency Domain Constraints for Physical Human-Robot Interaction" (4 citations), Chen introduces a gain-scheduled variable stiffness control method that reduces conservativeness while ensuring safety and adaptability during physical interaction. By integrating strict frequency-domain constraints, this work enhances the performance and reliability of human-robot systems. Chen’s research is pivotal for developing next-generation exoskeletons and collaborative robots, with her innovations directly impacting the fields of biomechanics, control theory, and assistive technology.
Research Focus
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Top Papers
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