Xunhe Yin
Papers
2
Total Citations
53
H-Index
2
About
Xunhe Yin is a researcher specializing in autonomous mobile robotics and intelligent control systems, with a particular focus on the intersection of machine learning and classical control theory. Yin's most recognized contribution to the field is the 2019 paper "Trajectory Tracking Control for Mobile Robots Using Reinforcement Learning and PID," which has garnered 50 citations and represents a notable effort to bridge the gap between modern reinforcement learning techniques and established proportional-integral-derivative (PID) control frameworks. This hybrid approach addresses one of the enduring challenges in robotics: enabling mobile robots to follow precise trajectories in dynamic and uncertain environments. By combining the adaptability of reinforcement learning with the reliability and interpretability of PID control, Yin's work offers a practical and robust solution attractive to both researchers and engineers. The subsequent 2020 correction paper demonstrates a commitment to scientific rigor and accuracy in published findings. While Yin's citation profile remains focused, the impact of this foundational work suggests a meaningful contribution to the growing body of research on intelligent robotic control, making it a valuable reference for students and practitioners exploring autonomous navigation systems.
Research Focus
Key Achievements
Top Papers
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