Mingwen Zheng
Papers
1
Total Citations
43
H-Index
1
About
Mingwen Zheng is a leading researcher in robotics and autonomous systems, with a primary focus on adaptive control, trajectory tracking, and vision-based navigation for mobile robots. Their most influential work, "Adaptive trajectory tracking of wheeled mobile robot based on fixed-time convergence with uncalibrated camera parameters" (2019, 43 citations), addresses a critical challenge in real-world robotics: achieving precise motion control despite uncertain or uncalibrated visual sensors. Zheng introduced a novel fixed-time convergence framework that ensures robots reach desired trajectories within a guaranteed time, independent of initial conditions—a significant advance over conventional asymptotic methods. This contribution has been widely cited by researchers working on robust control for autonomous vehicles, drone swarms, and industrial mobile platforms. Zheng’s work bridges theoretical control theory and practical deployment, offering solutions that are both mathematically rigorous and computationally efficient. Their research continues to influence the design of resilient, vision-guided systems capable of operating in unstructured environments, making them a key figure in the evolution of intelligent, adaptive robotics.
Research Focus
Key Achievements
Top Papers
- 1