Yujie Tang

Papers

Total Citations

H-Index

About

Yujie Tang is a rising star in robotics and autonomous systems, whose research centers on multi-robot collaboration, semantic mapping, and robust localization in complex environments. Her work bridges the gap between ground and aerial robots, enabling them to work together seamlessly for tasks like mapping and navigation. Tang’s most notable contribution is the development of the SAME framework (2024, 10 citations), a ground-air collaborative system that leverages multiple perspectives and high maneuverability to handle challenging environments. She has also pioneered methods for multi-view robust localization (2023, 9 citations), effectively filtering out outlier data associations in low-overlap, high-difference scenes to improve accuracy. Additionally, her SSGM approach (2023, 6 citations) introduces spatial semantic graph matching for loop closure detection, allowing robots to describe and recognize scenes more intelligently by capturing object semantics and topological relationships. With a focus on semantic features and graph-based techniques, Tang’s work is advancing the reliability and intelligence of multi-robot systems. Her achievements are particularly impactful for applications in search-and-rescue, exploration, and autonomous navigation, marking her as a key contributor to the next generation of collaborative robotics.