Duy Thao Nguyen

Vivekananda Global University, Le Quy Don Technical University

Papers

Total Citations

H-Index

About

Duy Thao Nguyen is a robotics researcher whose work bridges reinforcement learning and socially aware navigation for autonomous mobile robots. His most impactful contribution, "Model-based Q-learning for humanoid robots" (2017, 14 citations), proposes a reinforcement learning framework that applies Q-learning to humanoid locomotion. Nguyen validated this approach through both simulation and real-world experiments on the NAO robot, demonstrating how model-based methods can accelerate policy learning in complex robotic systems—a foundational step for adaptive, real-time control. Nguyen also advances socially compliant robot navigation in crowded, dynamic environments. In his 2021 papers, he introduces the Social Hybrid Reciprocal Velocity Obstacle (SHRVO) framework, which integrates social norms into motion planning to improve human-robot interaction. His comparative study of the HRVO model and the Social Force Model (SFM) provides critical insights into how robots can predict and respond to pedestrian flows, enhancing safety and naturalness in shared spaces. While these works have garnered modest citations (2 each), they represent emerging directions in human-aware robotics. Nguyen’s research is particularly relevant for students and engineers developing autonomous systems that must operate seamlessly alongside humans, from service robots to autonomous vehicles.