Papers
9
Total Citations
53
H-Index
4
About
Xia Yuan is a leading researcher in mobile robotics, specializing in perception, localization, and navigation for autonomous systems operating in complex outdoor environments. Her work bridges the gap between sensor fusion and real-time decision-making, with a particular focus on small ground robots constrained by limited computing resources. Yuan’s most influential contribution is her foundational work on Lidar scan-matching for mobile robot localization (2009, 24 citations), which established key techniques for accurate pose estimation using sparse point clouds. She has also advanced the field of robot vision by introducing the first RGB-D saliency detection dataset and algorithm tailored for robotic applications (2018, 9 citations), addressing a critical gap as depth sensors became ubiquitous. Her more recent innovations include a real-time road intersection detection algorithm using augmented viewpoints (2023) and a fuzzy SVM-based road detection method that fuses laser and image data (2015). Yuan’s work on obstacle detection through multi-sensor fusion (2015) and point cloud clustering for navigation (2011) further demonstrates her commitment to practical, computationally efficient solutions. Her ongoing research into cross-view pose estimation (2025) promises to enhance localization in GNSS-denied environments, cementing her reputation as a pioneer in field robotics perception.
Research Focus
Key Achievements
Top Papers
- 1Lidar Scan-Matching for Mobile Robot Localization24 citations · 2009
- 2RGB-D Saliency Detection: Dataset and Algorithm for Robot Vision9 citations · 2018
- 3
- 4
- 5
- 6A Laser Point Cloud Clustering Algorithm for Robot Navigation3 citations · 2011
- 7
- 8A probability distribution-based point cloud clustering algorithm2 citations · 2012
- 9Active layered topology mapping driven by road intersection1 citations · 2025