Papers
7
Total Citations
176
H-Index
6
About
Guoxing Bai is a leading researcher in the field of mobile robotics, specializing in advanced path tracking and autonomous navigation. His work centers on the application of Model Predictive Control (MPC) to solve critical challenges in wheeled, car-like, and tracked mobile robots, particularly under high-speed or hazardous conditions. Bai’s major contributions include pioneering anti-sideslip control strategies, as highlighted in his highly cited 2019 review on MPC-based path tracking (71 citations) and his 2019 paper on dynamic prediction models for wheeled robots (54 citations). He has also developed innovative methods to improve real-time performance, such as using neural networks trained on NMPC samples (13 citations), and has addressed practical deployment in unstructured environments, including emergency rescue scenarios under 6G networks (9 citations). His work on fuzzy MPC for sideslip mitigation and non-global coordinate system tracking further demonstrates his ability to tackle real-world constraints. With over 170 total citations, Bai’s research is essential reading for engineers and researchers working on autonomous vehicle control, offering robust solutions that bridge theoretical MPC with practical, safety-critical applications.
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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