Kuili Liu
Papers
1
Total Citations
5
H-Index
1
About
Kuili Liu is a robotics researcher whose work centers on advanced control strategies for autonomous mobile systems, particularly in uncertain and dynamic environments. Liu’s most notable contribution is the development of a novel robust hybrid controller that integrates mixed H₂/H∞ optimization with model predictive control for non-holonomic wheeled mobile robots. This approach addresses the critical challenge of path tracking under kinematic disturbances, enabling robots to maintain stability and precision in both known and unknown terrains. The 2021 paper detailing this method has garnered 5 citations, reflecting its emerging influence in the field of robotic control. Liu’s research is distinguished by its practical focus on real-world applicability, bridging theoretical control theory with tangible robotic performance. By tackling the complexities of disturbance rejection and trajectory accuracy, Liu has provided a foundational framework for future work in autonomous navigation, particularly for applications in logistics, exploration, and service robotics. This work positions Liu as a thoughtful contributor to the ongoing evolution of resilient, adaptive robotic systems.
Research Focus
Key Achievements
Top Papers
- 1