Phan Xuan Tan
Papers
12
Total Citations
117
H-Index
6
About
Phan Xuan Tan is an emerging researcher whose work sits at the dynamic intersection of computer vision, robotics, and autonomous systems. His research focuses primarily on mobile robot navigation, robotic manipulation, and deep learning-based perception, with particular emphasis on developing lightweight yet powerful neural network architectures deployable on resource-constrained platforms. Among his most notable contributions, Tan has advanced semantic segmentation for mobile robots through innovations like IRDC-Net and KD-SegNet, the latter leveraging knowledge distillation to achieve efficient real-world deployment. His hybrid path planning framework combining JBS-A* and improved Dynamic Window Approach demonstrates a sophisticated grasp of both global and local navigation challenges. In robotic manipulation, his vision-based pick-and-place systems and comprehensive RGB-D dataset for 6D pose estimation represent practical contributions bridging laboratory research and industrial application. Tan has also made meaningful strides in hand-object pose estimation using multimodal fusion techniques relevant to augmented reality and imitation learning. His work on adaptive nonlinear control for self-balancing robots further reflects his breadth across control theory and intelligent systems. With over 110 cumulative citations across publications spanning just 2023–2025, Tan has established a remarkably productive early research trajectory, making him a researcher worth following closely as autonomous robotics continues to evolve.
Research Focus
Key Achievements
Top Papers
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- 9Attention-Based Grasp Detection With Monocular Depth Estimation5 citations · 2024
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