Nguyen Trung Nguyen
Papers
2
Total Citations
23
H-Index
2
About
Nguyen Trung Nguyen is a robotics researcher whose work centers on advancing autonomous navigation and human-robot interaction in indoor environments. His primary research areas include 3D LiDAR-based pedestrian detection, Simultaneous Localization and Mapping (SLAM), and deep learning architectures for robotic perception. Nguyen’s major contributions are highlighted by his development of IRBGHR-PIXOR, a novel detection framework that enhances indoor robot pedestrian detection through improved PIXOR backbones and Gaussian heatmap regression—a method that significantly boosts accuracy and robustness in spatially constrained settings. His comparative analysis of SLAM algorithms, integrated with YOLO-based human detection and multi-optimization in ROS2, provides a practical blueprint for improving real-time robot performance. With his most-cited papers accumulating over 20 citations in just two years, Nguyen’s work is gaining rapid recognition for its direct applicability to safe, seamless indoor robotics. His research not only pushes the boundaries of perception and localization but also offers deployable solutions for robots sharing spaces with humans, making him a rising voice in the field of intelligent autonomous systems.
Research Focus
Key Achievements
Top Papers
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- 2