Jun‐Juh Yan

National Chin-Yi University of Technology, Shu-Te University, Northwestern Polytechnical University

Papers

Total Citations

H-Index

About

Jun‐Juh Yan is a robotics researcher whose work focuses on the nonlinear dynamics, control, and intelligent behavior of robotic systems. His major contributions span the design and stabilization of novel robotic platforms, including a self-bouncing and self-balancing cube robot, where he derived dynamic models using angular momentum conservation and torque equilibrium theory. He has also advanced multirobot coordination through distributed sliding-mode formation controllers, which robustly handle external disturbances and system uncertainties in wheeled mobile robots. Additionally, Yan explored machine learning for locomotion, developing an obstacle avoidance strategy for biped robots using fuzzy Q-learning. While his most-cited papers have modest citation counts (4–5 each), they represent foundational steps in specialized areas of robotics. His work is notable for integrating rigorous mathematical modeling with practical control implementation, contributing to the fields of nonlinear dynamics, distributed control, and reinforcement learning for autonomous systems.