Yanpeng Zhou
Papers
3
Total Citations
23
H-Index
3
About
Yanpeng Zhou is a rising researcher in robotics and neural network control, with a focus on solving complex kinematic problems for mobile manipulators. His work centers on developing advanced neural network models for real-time trajectory tracking and human-robot interaction. Zhou’s most impactful contribution is the introduction of a noise suppression zeroing neural network (NSZNN) for four-wheel mobile manipulators, which robustly handles external disturbances during inverse kinematics solving—a critical challenge in autonomous navigation and industrial automation. This work has already garnered 14 citations since its 2024 publication. Earlier, Zhou pioneered the use of wavelet neural networks (WNN) for continuous estimation of human knee-joint angles from surface electromyography (sEMG) signals, achieving 6 citations and demonstrating potential for prosthetic control and rehabilitation robotics. He also developed a gradient neural network (GNN) for time-varying inverse kinematics of four-wheel robotic arms, laying foundational work for his later innovations. Zhou’s research bridges theoretical neural dynamics with practical robotic systems, making him a notable contributor to the fields of neural robotics and human-machine interfaces.
Research Focus
Key Achievements
Top Papers
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