Xiangwei Wang
Papers
2
Total Citations
15
H-Index
2
About
Xiangwei Wang is an emerging researcher whose work sits at the intersection of autonomous systems, state estimation, and intelligent robotics. His most notable contribution to date is a 2024 paper introducing a fast and stable GNSS-LiDAR-inertial state estimator, which leverages an iterated error-state Kalman filter to achieve robust localization through a coarse-to-fine estimation framework — a meaningful advance in multi-sensor fusion for autonomous navigation that has already garnered 11 citations since publication. Alongside this, Wang has explored practical robotics applications in industrial settings, investigating the deployment of intelligent inspection robots on automated energy meter verification lines to address inefficiencies inherent in manual calibration workflows. This 2023 work highlights his interest in bridging theoretical robotics research with real-world industrial automation challenges. Though early in his research career, Wang's portfolio reflects a dual focus on precision sensor fusion methodologies and applied robotic systems, positioning him as a contributor to both foundational navigation technology and the growing field of smart industrial automation. His work will be of particular interest to students and researchers in SLAM, autonomous vehicles, and robotics engineering.
Research Focus
Key Achievements
Top Papers
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- 2