Yongxu He
Papers
2
Total Citations
23
H-Index
2
About
Dr. Yongxu He is a rising researcher at the dynamic intersection of adaptive control, robotics, and machine learning, with a core focus on achieving high-precision autonomy for complex, uncertain systems. Dr. He’s most cited work, "Adaptive Robust Control of Uncertain Euler–Lagrange Systems Using Gaussian Processes" (2022, 20 citations), introduces a novel framework that fuses traditional robust control with Gaussian process regression. This approach allows robotic systems—ranging from manipulators to underwater vehicles—to learn and compensate for unknown dynamics and time-varying disturbances in real-time, significantly enhancing tracking accuracy. Building on this foundation, Dr. He’s recent work, "Double-loop Human-Robot Shared Control for Trajectory Tracking of an Underwater Robot" (2023), tackles the critical challenge of balancing autonomous precision with human teleoperation. By structuring control as a double-loop system, this research enables safer and more intuitive human-robot collaboration in unpredictable environments like the deep sea. Dr. He’s contributions are pioneering the next generation of robust, learning-enabled controllers, promising to make autonomous systems more reliable and adaptable in real-world, high-stakes applications.
Research Focus
Key Achievements
Top Papers
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- 2