Boyu Shu
Papers
1
Total Citations
11
H-Index
1
About
Boyu Shu is a rising researcher at the intersection of robotics, energy systems, and intelligent control. His work focuses on solving critical challenges in legged robot autonomy, particularly the development of reliable energy supply systems and adaptive energy management strategies for robots with highly variable power demands. Shu’s most-cited paper, "Learning-Based Model Predictive Control for Legged Robots with Battery–Supercapacitor Hybrid Energy Storage System" (2025, 11 citations), introduces a novel approach that combines learning-based methods with model predictive control to optimize hybrid energy storage in electrically driven legged robots. This contribution addresses a pressing gap in the field, as traditional energy systems often fail to meet the dramatic power fluctuations of dynamic locomotion. By integrating battery-supercapacitor systems with intelligent control, Shu’s work paves the way for more efficient, long-endurance robotic platforms. Though early in his career, his research has already garnered attention for its practical implications in robotics and energy management. Shu’s innovative fusion of control theory and machine learning marks him as a promising voice in the next generation of robotics engineers.
Research Focus
Key Achievements
Top Papers
- 1