Quang Vinh Tran
Vietnam National University, Hanoi, VNU University of Science
Papers
2
Total Citations
13
H-Index
2
About
Quang Vinh Tran is a robotics researcher whose work centers on solving the fundamental challenge of mobile robot localization—the problem of enabling a robot to determine its position within an unknown environment. His research integrates advanced sensor fusion and intelligent filtering techniques to achieve this. Tran’s most significant contribution is the development of a Fuzzy Neural Network-based Extended Kalman Filter (FNN-EKF), which dramatically improves localization accuracy by combining neural network adaptability with the predictive power of the Kalman filter. This work, published in 2012, remains his most cited paper with 9 citations. In a complementary study, he demonstrated a multi-sensor approach, fusing data from a laser range finder (LRF) and an omni-directional camera within an EKF framework to localize a unicycle-like robot. By leveraging line segment features from LRF scans and visual data, this system achieved robust performance in complex settings. Tran’s research provides a practical, intelligent framework for autonomous navigation, offering a clear path for students and engineers working on real-world robotic systems that must operate reliably without pre-mapped environments.
Research Focus
Key Achievements
Top Papers
- 1
- 2