XU Wen-bo

Beijing Jingshida Electromechanical Equipment Research Institute, Jiangnan University, Institute of Information Engineering

Papers

Total Citations

H-Index

About

Dr. Xu Wen-bo is a robotics researcher whose work bridges intelligent control, neural networks, and reinforcement learning. His primary research areas include adaptive robot control, fuzzy neural networks, and Q-learning for autonomous navigation. Dr. Xu’s most significant contribution is the development of a modal space neural network compensation control for Gough-Stewart robots handling uncertain loads—a breakthrough that addresses critical stability challenges in parallel robotics. This work, published in 2021, has already garnered 39 citations, reflecting its immediate impact on the field. In earlier foundational work, Dr. Xu pioneered the integration of fuzzy Q-learning into continuous state and action spaces, enabling mobile robots to navigate without prior environmental knowledge. His 2010 paper on wall-following control demonstrated how fuzzy neural networks could directly approximate Q-value functions, allowing robots to learn optimal navigation policies through optimization-based greedy action selection. This innovative approach to reinforcement learning in robotics has influenced subsequent research in autonomous navigation and adaptive control systems. Dr. Xu’s work continues to shape how robots learn and adapt in uncertain, real-world environments.