Papers
6
Total Citations
255
H-Index
4
About
Yigang Cen is a leading researcher in robotics, computer vision, and 3D point cloud deep learning, with a career spanning foundational work in mobile robotics to cutting-edge self-supervised learning. His early landmark contribution, "Path planning for mobile robot using the particle swarm optimization with mutation operator" (2005, 141 citations), introduced a novel optimization approach for real-time robot navigation, establishing a widely cited framework in autonomous systems. Cen has since advanced pedestrian detection in low-quality imagery through super-resolution reconstruction (2021, 63 citations), significantly improving safety in autonomous driving and surveillance. His work on action recognition for robotics and manufacturing automation (2021, 35+ citations) leverages 3D binary micro-block differences to enable efficient human-robot interaction. Most recently, Cen has pioneered self-supervised representation learning for 3D point clouds with DCPoint (2024), addressing the critical bottleneck of labeled data scarcity in deep networks. He has also contributed comprehensive surveys on attention models for point clouds, guiding researchers in this rapidly evolving field. With over 250 citations across his most influential works, Cen’s research continues to shape practical applications in autonomous driving, robotics, and manufacturing automation.
Research Focus
Key Achievements
Top Papers
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- 5Attention Models for Point Clouds in Deep Learning: A Survey4 citations · 2021
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