Thuong Ngoc-Cong Tran
Papers
2
Total Citations
109
H-Index
2
About
Dr. Thuong Ngoc-Cong Tran is a leading researcher in precision robotics, specializing in robot calibration and positioning accuracy. His work focuses on integrating advanced neural networks with bio-inspired optimization algorithms to dramatically improve the absolute pose and position accuracy of industrial robots. Dr. Tran’s most influential contribution is a novel calibration method combining an Extended Kalman Filter with an artificial neural network trained by a butterfly and flower pollination algorithm (ANN-BFPA), which has garnered 82 citations for its effectiveness in correcting geometric errors. He further advanced the field with a method employing Levenberg-Marquardt accelerated particle swarm optimization (LMAPSO), cited 27 times, demonstrating his sustained impact on enhancing robotic precision. By fusing machine learning with nature-inspired computation, Dr. Tran’s work directly addresses critical limitations in manufacturing and automation, enabling robots to achieve higher fidelity in tasks requiring micron-level accuracy. His research is essential reading for engineers and scientists seeking to push the boundaries of robotic performance through intelligent, data-driven calibration techniques.
Research Focus
Key Achievements
Top Papers
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