Kaihui Zhao
Papers
1
Total Citations
5
H-Index
1
About
Kaihui Zhao is a researcher whose work lies at the intersection of robotics, adaptive control, and machine learning, with a particular focus on precision manufacturing. Their key research areas include trajectory tracking, sliding mode control (SMC), and the compensation of nonlinear actuator dynamics in industrial robots. Zhao’s major contribution is the development of a robust adaptive trajectory tracking algorithm for free-form surface grinding robots (FFSGRs) that effectively mitigates the detrimental effects of asymmetric actuator dead zones—a common and challenging issue in grinding processes that directly impacts workpiece quality. By integrating SMC with machine learning techniques, their 2019 paper provides a novel solution that enhances both the accuracy and robustness of robotic grinding systems. While the work has garnered 5 citations, its significance lies in addressing a critical gap in industrial robotics, offering a practical pathway to higher-precision automated manufacturing. Zhao’s research is particularly notable for bridging theoretical control methods with real-world industrial constraints, making it valuable for engineers and researchers working on advanced robotic applications in manufacturing and surface finishing.
Research Focus
Key Achievements
Top Papers
- 1