Linlin Xia
Papers
8
Total Citations
153
H-Index
5
About
Linlin Xia is a leading researcher in autonomous mobile robotics, with a primary focus on simultaneous localization and mapping (SLAM) and multi-sensor fusion for robot navigation. Her work bridges the gap between geometric and semantic scene understanding, pioneering application-oriented solutions that enable robots to perceive and navigate complex environments more intelligently. Xia’s most influential contribution is her comprehensive survey on image semantics-based visual SLAM (63 citations), which established a foundational framework for integrating semantic information into traditional SLAM pipelines. She has also made significant advances in visual-inertial odometry (VIO), developing tightly-coupled systems that fuse point and line features for robust navigation in GPS-denied environments, as demonstrated in her highly cited 2022 work (39 citations). Her innovative use of polarized light as a navigation cue, combined with graph optimization for global heading estimation, represents a novel approach to outdoor robot localization. Beyond SLAM, Xia has contributed to path planning through adaptive genetic algorithms and fault diagnosis in inertial measurement units using deep belief networks. Her research, spanning over a decade from 2010 to 2024, consistently addresses real-world robotic challenges, from patrol robot navigation to complex surface machining, making her work highly relevant for both academic researchers and industry practitioners seeking practical, deployable solutions for autonomous systems.
Research Focus
Key Achievements
Top Papers
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- 3Adaptive Genetic Algorithm Enhancements for Path Planning of Mobile Robots18 citations · 2010
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