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About

Renzhen Chen is a robotics researcher specializing in variable stiffness actuators, dual-inertia system dynamics, and power line inspection robots. Their work focuses on enhancing the safety and performance of human-robot interaction systems, particularly for medical rehabilitation robots, exoskeletons, and legged mobile robots. Chen’s most cited paper, “Dynamic performance analysis of the variable stiffness actuator considering gap and friction characteristics based on two-inertia-system” (2021, 32 citations), provides foundational insights into actuator dynamics. They further advanced this area with “Transmission friction measurement and suppression of dual-inertia system based on RBF neural network and nonlinear disturbance observer” (2022, 25 citations), introducing intelligent control methods to improve actuator precision. In robotics applications, Chen contributed “The climbing performance analysis of a robot for power line inspection with retractable double serial manipulators” (2021, 12 citations), addressing the challenging obstacle of strain clamps in power line maintenance. Their notable work “A new low-energy nonlinear variable stiffness actuator for the knee joint” (2022, 8 citations) demonstrates a practical innovation for energy-efficient assistive devices. With over 77 cumulative citations, Chen’s research bridges theoretical actuator design and real-world robotic applications, making meaningful contributions to safer, more capable human-robot interaction systems.