Jinchi Xu
Papers
4
Total Citations
74
H-Index
4
About
Jinchi Xu is a researcher advancing the frontiers of robotic actuation and control, with a focus on the dynamic performance and precision of variable stiffness actuators and flexible joint systems. His work addresses critical challenges in human-robot interaction, particularly for medical rehabilitation robots, legged mobile robots, and exoskeleton-assisted devices. Xu has made notable contributions by modeling and mitigating nonlinear effects such as gear angle error and friction interference in dual-inertia systems. He developed a control method for manipulator flexible joints using a BP neural network-tuned PI controller, and proposed a novel low-energy nonlinear variable stiffness actuator for the knee joint, enhancing safety and efficiency. His research on transmission friction measurement and suppression, employing RBF neural networks and nonlinear disturbance observers, has been widely recognized. With over 70 citations across his most-cited papers, Xu’s work is foundational for improving the performance, stability, and energy efficiency of next-generation robotic systems, making him a key figure in the development of safer, more responsive robotic joints.
Research Focus
Key Achievements
Top Papers
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