Nguyen Thanh Nam
Papers
2
Total Citations
10
H-Index
1
About
Nguyen Thanh Nam is a robotics researcher whose work centers on intelligent control systems and real-time perception for autonomous robots. His primary research areas include pneumatic artificial muscle (PAM) actuation, adaptive neural network control, and computer vision for robotic sports. Nam’s most significant contribution is the development of a neural-based feed-forward PID direct force control (FNN-PID-DF) approach for highly nonlinear 2-axes PAM manipulators. This work, published in 2018 and cited 9 times, demonstrates a novel method to substantially improve force output performance in soft robotic systems, addressing a key challenge in compliant actuation. More recently, Nam has applied his expertise to the RoboCup Small Size League (SSL), conducting an empirical study on one-stage object detection methods. This 2022 work, already receiving 1 citation, explores state-of-the-art real-time detection models to enhance the speed and accuracy of soccer robots’ visual perception, directly supporting the development of competitive game strategies. By bridging advanced control theory with practical robotic vision, Nam’s research contributes to both the foundational understanding of soft manipulator control and the applied advancement of autonomous sports robotics.
Research Focus
Key Achievements
Top Papers
- 1
- 2