Papers
6
Total Citations
173
H-Index
6
About
Qing Gu is a leading researcher in autonomous mobile robotics, with a primary focus on path tracking control for wheeled and tracked robots operating under challenging, real-world conditions. Her work centers on advancing Model Predictive Control (MPC) to address critical issues of safety and stability, particularly the dangerous problem of sideslip during high-speed turns. Gu’s major contributions include the development of anti-sideslip fuzzy MPC and dynamic prediction models that account for non-holonomic constraints and centrifugal forces, directly improving robot safety. Her 2019 review on MPC-based path tracking has garnered 71 citations, establishing a foundational reference in the field. She has also pioneered innovative hybrid approaches, such as using neural networks trained by nonlinear MPC samples to overcome real-time performance bottlenecks, and designing preview linear MPC for autonomous driving in unstructured emergency rescue scenarios, including under 6G networks. With over 170 total citations across her key works, Gu’s research bridges theoretical control advances with practical applications in mining, indoor navigation, and emergency response, making her a notable figure in intelligent vehicle control.
Research Focus
Key Achievements
Top Papers
- 1Review and Comparison of Path Tracking Based on Model Predictive Control71 citations · 2019
- 2Path Tracking of Wheeled Mobile Robots Based on Dynamic Prediction Model54 citations · 2019
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