Papers
1
Total Citations
10
H-Index
1
About
Hongyu Lin is a researcher specializing in intelligent control systems and robotics, with a particular focus on self-balancing and autonomous vehicle technologies. Their most-cited work, "Combined control algorithm based on synchronous reinforcement learning for a self-balancing bicycle robot" (2023), has garnered 10 citations and represents a significant contribution to the field of dynamic stabilization. In this study, Lin proposed a novel hybrid control framework that integrates synchronous reinforcement learning with traditional control methods, enabling a bicycle robot to maintain balance and navigate autonomously under varying conditions. This work not only advances the practical application of reinforcement learning in real-time robotics but also offers a scalable solution for two-wheeled autonomous systems. Lin’s research bridges the gap between theoretical machine learning and physical robot control, demonstrating how adaptive algorithms can enhance stability and performance in complex, nonlinear environments. Their contributions are particularly relevant for students and researchers exploring the intersection of control theory, artificial intelligence, and mechatronics, providing a foundation for future innovations in autonomous transportation and assistive robotics.
Research Focus
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Top Papers
- 1