Xu Wang

University of Science and Technology Beijing

Papers

Total Citations

H-Index

About

Xu Wang is a researcher specializing in mobile robotics, autonomous navigation, and sensor fusion, with a particular focus on LiDAR-inertial systems for localization and mapping. His most notable contribution lies in advancing the robustness of simultaneous localization and mapping (SLAM) frameworks through rigorous treatment of outlier data — a challenge frequently overlooked in the field. In his 2021 work, "A Robust Lidar-Inertial Localization System Based on Outlier Removal," Wang addresses a critical gap in existing LiDAR-inertial odometry pipelines by demonstrating how unmitigated outliers can significantly degrade trajectory accuracy, particularly during rapid rotational movements. By integrating outlier removal strategies into the localization framework, he enhances the reliability and precision of state estimation for mobile robotic platforms operating in complex, real-world environments. With 4 citations already accrued, his research is beginning to attract attention from the robotics and autonomous systems community. Wang's work represents a meaningful step forward in making sensor-fused localization systems more resilient and deployment-ready, contributing valuable insights to researchers and engineers working on next-generation autonomous vehicles and robotic navigation solutions.