Limin Huang
Papers
1
Total Citations
7
H-Index
1
About
Limin Huang is a leading researcher in rehabilitation robotics and intelligent control systems, with a focus on developing advanced motion control strategies for assistive technologies. Their most-cited work, "Research on the Motion Control Strategy of a Lower-Limb Exoskeleton Rehabilitation Robot Using the Twin Delayed Deep Deterministic Policy Gradient Algorithm" (2024), has already garnered 7 citations, showcasing its early impact. In this study, Huang pioneered the application of the Twin Delayed Deep Deterministic Policy Gradient (TD3) algorithm to design a motion controller for lower-limb exoskeleton rehabilitation robots (LLERRs), enabling more precise and adaptive assistance for patients undergoing lower-limb rehabilitation exercises. This contribution addresses critical challenges in human-robot interaction, enhancing the safety and efficacy of robotic rehabilitation. Huang’s work bridges reinforcement learning and biomedical engineering, offering a novel framework that improves patient outcomes and autonomy. Their research is highly relevant for students and researchers in robotics, AI, and rehabilitation medicine, providing a foundation for future innovations in exoskeleton control and personalized therapy.
Research Focus
Key Achievements
Top Papers
- 1