Papers
5
Total Citations
54
H-Index
4
About
Yingwei Xia is a robotics researcher specializing in visual navigation, state estimation, and multi-sensor fusion for autonomous mobile robots. His work addresses critical challenges in robot autonomy, particularly in complex and unstructured environments. Xia’s most cited paper, “Object-Based Reliable Visual Navigation for Mobile Robot” (2022, 24 citations), introduces a perception-aware navigation method that overcomes the limitations of prior map-based and learning-based approaches, enhancing reliability without extensive training. He also developed “VINS-MKF” (2018, 13 citations), a tightly-coupled multi-keyframe visual-inertial odometry system that significantly improves state estimation accuracy and robustness under challenging conditions like limited field of view. Xia’s contributions extend to precise sensor synchronization with his IEEE 1588-based method (2019, 9 citations), which ensures accurate timestamping for multi-sensor fusion—a cornerstone for modern robotic systems. Additionally, his work on online self-calibration for multi-camera visual-inertial SLAM (2018, 4 citations) and a cable-driven robot arm for visual tracking in Tokamak vacuum vessels (2018, 4 citations) showcases his versatility in both algorithmic and hardware innovations. With a growing citation impact, Xia’s research is pivotal for advancing reliable, real-world robot navigation and perception.
Research Focus
Key Achievements
Top Papers
- 1Object-Based Reliable Visual Navigation for Mobile Robot24 citations · 2022
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- 5A Cable-Driven Robot Arm for Visual Tracking in Tokamak Vacuum Vessel4 citations · 2018