Do Nam Thang
Papers
2
Total Citations
11
H-Index
2
About
Do Nam Thang is a researcher at the forefront of socially aware mobile robotics, specializing in the integration of deep learning and reinforcement learning to create robots that navigate safely and intuitively alongside humans. His work addresses the critical challenge of enabling robots to perceive and respond to dynamic social environments. Thang’s most impactful contribution, a deep learning-based system for multiple objects detection and tracking (9 citations), provides the foundational perception layer essential for socially aware navigation frameworks. Building on this, his recent research pioneers the use of multi-objective deep reinforcement learning to balance competing priorities—such as safety, efficiency, and social compliance—in robot navigation. This novel approach overcomes the limitations of single-objective methods, allowing for more nuanced and adaptable policies in complex human spaces. By tackling the multi-objective nature of social navigation, Thang is advancing the development of robots that can seamlessly integrate into crowded, human-centric environments, marking a significant step toward truly autonomous and socially intelligent mobile robots.
Research Focus
Key Achievements
Top Papers
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- 2