Papers
1
Total Citations
10
H-Index
1
About
Xudong Zheng is an emerging researcher specializing in intelligent control systems and autonomous mobile robotics, with a particular focus on the challenging domain of underactuated robotic platforms. His most recognized work addresses one of robotics' inherently difficult problems: maintaining dynamic balance in reaction wheel bicycle robots navigating curved pavements under real-world conditions. This research is notable for its innovative application of online series-parallel reinforcement learning to compensate for inaccurate model parameters, model uncertainties, and external disturbances — conditions that render traditional control approaches inadequate. By tackling both lateral instability and the underactuated nature of bicycle robots simultaneously, Zheng's framework demonstrates a practical pathway toward deploying unmanned mobile robots in complex, unstructured environments. His work, which has accumulated 10 citations since its 2023 publication, reflects growing community interest in data-driven adaptive control strategies for nonlinear robotic systems. For students and researchers working at the intersection of reinforcement learning and robotics control theory, Zheng's contributions offer a compelling example of how machine learning techniques can be integrated with classical control frameworks to solve real-world engineering challenges in autonomous mobility.
Research Focus
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Top Papers
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