Papers

2

Total Citations

35

H-Index

2

About

Yahui Dong is a robotics researcher whose work focuses on advancing trajectory tracking and control for wheeled mobile robots, with a particular emphasis on geometric methods that respect the underlying manifold structure of robotic configurations. Their major contribution is the development of Geometric Model Predictive Control (GMPC), a framework that explicitly accounts for the continuous transformation groups governing robot motion—an often-overlooked constraint in conventional optimization approaches that treat robot states as simple vector spaces. This innovation has already garnered significant attention, with their 2024 paper "GMPC: Geometric Model Predictive Control for Wheeled Mobile Robot Trajectory Tracking" accumulating 32 citations in a short time, signaling strong impact in the control and robotics communities. By bridging geometric control theory with practical model predictive control, Dong’s work offers more accurate and stable trajectory tracking for wheeled robots operating in real-world environments. Their research is particularly relevant for students and engineers working on autonomous navigation, robot dynamics, and nonlinear control, providing a principled alternative to naive Euclidean-space methods. With this foundational contribution, Yahui Dong is establishing themselves as a rising voice in geometric robotics and model-based control.

Research Focus

Key Achievements

2
H-Index
2
Papers
35
Total Citations
18
Avg Citations/Paper
🏆 Most Cited Paper
GMPC: Geometric Model Predictive Control for Wheeled Mobile Robot Trajectory Tracking
32 citations · 2024
📈 Most Prolific Year: 2024 (2 Papers)
🤝 Key Collaborators: 9
🏛 Institutions: Hong Kong University of Science and Technology

Top Papers

  1. 1
  2. 2

Key Collaborators

Contact & Links

Available for collaboration
Content generated · 13 days ago