Papers
8
Total Citations
69
H-Index
5
About
Yufei Zhou is a rising roboticist whose research focuses on the dynamic identification, kinematic calibration, and intelligent control of industrial and space manipulators. His work addresses critical challenges in precise robot control, particularly through novel approaches that integrate nonlinear friction models and advanced optimization algorithms. Zhou's most cited paper, "A Semilinearized Approach for Dynamic Identification of Manipulator Based on Nonlinear Friction Model" (2024, 24 citations), presents a breakthrough method for accurate parameter estimation, directly improving robotic performance in real-world applications. He has also made significant contributions to human-robot collaboration, proposing a four-level control framework for dual-arm manipulators (2025, 8 citations), and to collision detection through nonlinear momentum observers (2024, 6 citations). Zhou's innovative use of reinforcement learning for variable admittance control in dynamic environments (2022, 2 citations) and his end-to-end visual servoing controller employing soft-actor-critic algorithms (2025, 6 citations) demonstrate his versatility in merging learning-based methods with traditional control theory. His work on adaptive fuzzy integral sliding mode control for free-floating close-chain manipulators (2024, 4 citations) highlights his engagement with the unique challenges of space robotics. With a growing portfolio of high-impact publications, Zhou is establishing himself as a key contributor to the next generation of intelligent, adaptive robotic systems.
Research Focus
Key Achievements
Top Papers
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