Jing‐Feng Li
Papers
2
Total Citations
6
H-Index
2
About
Jing‐Feng Li is a leading researcher in intelligent robotics and human–machine interaction, with a primary focus on rehabilitation robotics and soft tactile sensing. His most influential work addresses the critical challenge of gait trajectory tracking in lower-limb exoskeletons for stroke and spinal cord injury patients. In a 2025 study, Li proposed a novel iterative learning control strategy integrated with an RBF neural network to manage nonlinear perturbations in muscle groups and gait irregularities, achieving precise, adaptive control for a 13-degree-of-freedom rehabilitation robot. This contribution has already garnered 4 citations, signaling its immediate impact on the field. Additionally, Li developed a super-hydrophobic tactile sensor designed for damage-free fruit grasping, demonstrating his versatility in applying robotic sensing to agricultural automation. This work, with 2 citations, showcases his ability to bridge soft robotics and practical manipulation. Li’s research is notable for its direct clinical relevance and innovative control methodologies, positioning him as a rising figure in rehabilitation engineering and intelligent robotic systems.
Research Focus
Key Achievements
Top Papers
- 1
- 2A super-hydrophobic tactile sensor for damage-free fruit grasping2 citations · 2025