Pham Trung Dung
Papers
3
Total Citations
21
H-Index
2
About
Pham Trung Dung is a robotics researcher whose work focuses on the critical challenge of enabling autonomous mobile robots to navigate safely and intelligently in dynamic, human-populated environments. His research integrates multiple sensor fusion, deep learning, and reinforcement learning to advance robot perception and decision-making. Dung’s most cited paper (2019, 10 citations) proposes a multi-sensor fusion method to significantly improve the accuracy of robot localization systems, a foundational component for reliable navigation. In another influential work (2018, 9 citations), he developed a deep learning-based system for detecting and tracking multiple objects, including humans, which is essential for socially aware robot navigation—allowing robots to move courteously and safely around people. His earlier research (2017) extended navigation frameworks by incorporating reinforcement learning, enabling robots to adapt their paths based on the relative motion of surrounding objects. Together, these contributions address the core tension between robust localization and responsive social interaction, marking Dung as a key contributor to the next generation of intelligent, human-aware mobile robotics.
Research Focus
Key Achievements
Top Papers
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