Papers
16
Total Citations
206
H-Index
8
About
Houcheng Li is a robotics and human-robot interaction researcher whose work spans rehabilitation engineering, exoskeleton design, and intelligent control systems. His research focuses on developing wearable assistive devices, learning from demonstration frameworks, and safe physical human-robot interaction — areas where he has made substantial contributions to both theory and practical application. Li's most recognized work involves the design of underactuated finger and hand exoskeletons for assisting elderly and motor-impaired individuals with daily grasping tasks, earning over 40 citations and demonstrating strong real-world relevance. His parallel work on passive model-predictive impedance control (34 citations) addresses critical safety challenges in human-robot collaboration, while his neural network-based framework for variable impedance skill learning (30 citations) advances robot adaptability through demonstration-based training. Beyond hardware, Li has contributed meaningfully to the theoretical foundations of stable dynamic systems, proposing Lyapunov-grounded approaches for learning point-to-point motions reliably. His more recent investigations into personalized musculoskeletal modeling using surface EMG signals and hybrid controllers for industrial musculoskeletal robots reflect an expanding research vision bridging biomechanics, manufacturing, and intelligent robotics. With a growing citation record exceeding 190 across a decade of work, Li represents a versatile and impactful voice in assistive and collaborative robotics research.
Research Focus
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