Papers
7
Total Citations
50
H-Index
5
About
Yipeng Yang is a robotics and control systems researcher whose work bridges intelligent automation, fuzzy optimization, and adaptive control for complex robotic platforms. His research primarily focuses on model predictive control (MPC), multi-objective fuzzy optimization, and trajectory planning for manipulators operating in uncertain environments. Yang’s most cited paper, “Adaptive Dynamic Coupling Control of Hybrid Joints of Human-Symbiotic Wheeled Mobile Manipulators with Unmodelled Dynamics” (2010, 12 citations), addresses the challenge of controlling human-robot collaborative systems under dynamic uncertainties. He further advanced robotic autonomy with “A trajectory planning method for robot scanning system using mask R-CNN for scanning objects with unknown model” (2020, 11 citations), integrating deep learning with motion planning for industrial inspection. His foundational work on receding horizon fuzzy optimization (2004, 10 citations) systematically solved constrained optimal control problems, influencing both theoretical MPC and practical robot path planning. Yang also contributed to aerial manipulation with a nonlinear disturbance observer-based adaptive backstepping controller (2020, 4 citations), enhancing trajectory tracking for Stewart-platform-based aerial manipulators. With a career spanning two decades, Yang’s work has shaped intelligent control strategies for human-symbiotic systems, autonomous scanning, and constrained optimization, earning recognition for its practical impact on industrial robotics and manufacturing.
Research Focus
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- 7An Automatic Laser Scanning System for Objects with Unknown Model2 citations · 2019