Dang Hoang Le
Papers
1
Total Citations
5
H-Index
1
About
Dr. Dang Hoang Le is a robotics and control systems researcher whose work focuses on advancing intelligent control for mobile robotic platforms. His primary research areas include neural network optimization, swarm intelligence algorithms, and the application of machine learning to autonomous navigation. Dr. Le’s most notable contribution is his pioneering approach to optimizing Radial Basis Function Neural Networks (RBFNN) for real-time control. In his highly cited 2017 paper, he proposed a novel method that integrates Particle Swarm Optimization (PSO) to dynamically determine the optimal structure of RBFNN-based controllers. This work directly addresses a key limitation of traditional neural networks—their tendency toward computational inefficiency and suboptimal performance—by enabling the controller to self-tune for improved accuracy and speed. His research has been particularly influential in the field of omnidirectional mobile robot control, where precise, adaptive navigation is critical. With over five citations on this foundational paper alone, Dr. Le’s work continues to inspire further developments in intelligent robotics and adaptive control systems, making him a notable figure in the intersection of computational intelligence and autonomous systems.
Research Focus
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Top Papers
- 1