Papers
2
Total Citations
4
H-Index
2
About
Xue Wan is a robotics researcher specializing in computer vision for autonomous systems, with a focus on space robotics and mobile robot localization. Her work addresses critical challenges in visual perception for dynamic environments, particularly in on-orbit satellite operations and ground-based robotic navigation. Wan's research on "Saliency and Tracking based Semi-supervised Learning for Orbiting Satellite Segmentation" (2019, 2 citations) introduces innovative methods for segmenting freely moving satellites against rapidly changing backgrounds—a fundamental capability for autonomous space repair and manipulation. Her contributions to mobile robot localization are demonstrated in "The Comparison between FTF-VO and MF-VO for High Accuracy Mobile Robot Localization" (2018, 2 citations), where she developed two visual odometry approaches (frame-to-frame and multi-frame) incorporating an ARFM-based 3D reconstruction method for enhanced SLAM accuracy. While her citation counts reflect an emerging career, Wan's work sits at the intersection of space robotics and autonomous navigation, addressing the practical challenges of real-time visual tracking in unstructured environments. Her research holds particular significance for advancing autonomous capabilities in space operations and terrestrial robotics, making her a promising contributor to the field of intelligent robotic perception.
Research Focus
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Top Papers
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