Minh Tuan Pham
Papers
1
Total Citations
5
H-Index
1
About
Minh Tuan Pham is a robotics researcher whose work centers on intelligent control systems for autonomous mobile robots, with a particular focus on trajectory tracking and nonholonomic constraint navigation. His most cited paper, "Trajectory tracking control of a mobile robot by computed torque method with on-line learning neural network" (2013), introduces a novel two-loop control algorithm that combines kinematic modeling with Lyapunov theory to generate precise velocity commands, while integrating an online learning neural network to adapt to dynamic environments. This approach has garnered 5 citations and represents a foundational contribution to adaptive robot control. Pham's research bridges theoretical control methods with practical implementation, addressing the challenge of real-time trajectory tracking under uncertain conditions. His work is particularly relevant for students and researchers interested in mobile robotics, neural network-based control, and autonomous navigation systems. By demonstrating how computed torque methods can be enhanced with machine learning, Pham has contributed to the development of more robust and adaptive robotic platforms capable of operating in complex, unstructured environments.
Research Focus
Key Achievements
Top Papers
- 1