Yifeng Guo
Papers
2
Total Citations
10
H-Index
2
About
Yifeng Guo is a leading researcher in the field of rehabilitation robotics, with a primary focus on the development and control of lower-limb exoskeleton systems. His work is dedicated to enhancing the quality of life for patients undergoing physical therapy by creating intelligent, adaptive robotic aids. Guo’s major contributions lie in pioneering advanced control algorithms for these systems. He has notably applied the Twin Delayed Deep Deterministic Policy Gradient (TD3) algorithm to design a sophisticated motion controller for a lower-limb exoskeleton rehabilitation robot (LLERR), a study that has already garnered 7 citations since its publication in 2024. Furthermore, he has tackled the critical challenge of consistency tracking in lower-limb rehabilitation robotic systems (LLRRS). By employing a closed-loop iterative learning control strategy, his 2025 paper addresses the complex issue of initial state deviations, ensuring that all system variables—from initial position to angular velocity—converge reliably. This work, with 3 recent citations, underscores his commitment to solving real-world control problems. Through these innovative approaches, Yifeng Guo is significantly advancing the precision and efficacy of robotic rehabilitation, making therapy more consistent and effective for patients.
Research Focus
Key Achievements
Top Papers
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- 2