Huy Anh Bui
Papers
1
Total Citations
3
H-Index
1
About
Huy Anh Bui is a robotics researcher whose work focuses on advancing autonomous navigation through deep reinforcement learning. His primary research areas include mobile robot control, distributional reinforcement learning, and safe navigation in uncertain environments. Bui’s major contribution lies in developing a novel navigation framework that leverages distributional deep reinforcement learning, which moves beyond traditional expected-value approaches to model the full distribution of possible outcomes. This innovation enables mobile robots to better handle unpredictable scenarios—such as sudden obstacles—by capturing the inherent uncertainty in dynamic environments. His most-cited paper, "Develop A Navigation Approach for Mobile Robots Based on the Distributional Deep Reinforcement Learning Framework" (2024), has already garnered 3 citations, signaling early impact in the field. This work addresses a critical limitation of conventional reinforcement learning, where expected values may fail to reflect real-world variability. By pioneering distributional methods for robotics, Bui is contributing to more robust and adaptive autonomous systems, with potential applications in service robots, autonomous vehicles, and industrial automation. His research offers a promising direction for creating robots that can navigate safely and effectively in complex, unpredictable settings.
Research Focus
Key Achievements
Top Papers
- 1