Xiaozhi Qu — accepted AI-conference papers

2025

An End-to-End Learning-Based Multi-Sensor Fusion for Autonomous Vehicle Localization

Changhong Lin, Jiarong Lin, Zhiqiang Sui, XiaoZhi Qu, Rui Wang, Kehua Sheng +1

ICRA 2025

Multi-sensor fusion is essential for autonomous vehicle localization, as it is capable of integrating data from various sources for enhanced accuracy and reliability. The accuracy of the integrated location and orientation depends on the precision of the uncertainty modeling. Traditional methods of

Cited by 2 Source ↗Scholar ↗

2018

A robust pose graph approach for city scale LiDAR mapping

Sheng Yang, Xiaoling Zhu, Xing Nian, Lu Feng, Xiaozhi Qu, Teng Ma

IROS 2018poster

This paper presents a method for reconstructing globally consistent 3D High-Definition (HD) maps at city scale. Current approaches for eliminating cumulative drift are mainly based on the pose graph optimization under the constraint of scan-matching factors. The misaligned edges in the graph may hav…

Cited by 64 Source ↗Scholar ↗