Xupeng Xie — accepted AI-conference papers

2025

AKF-LIO: LiDAR-Inertial Odometry with Gaussian Map by Adaptive Kalman Filter

Xupeng Xie, Ruoyu Geng, Jun Ma, Boyu Zhou

IROS 2025

Existing LiDAR-Inertial Odometry (LIO) systems typically use sensor-specific or environment-dependent measurement covariances during state estimation, leading to laborious parameter tuning and suboptimal performance in challenging conditions (e.g., sensor degeneracy and noisy observations). Therefor

Cited by 2 Source ↗code ↗Scholar ↗

2022

FusionPortable: A Multi-Sensor Campus-Scene Dataset for Evaluation of Localization and Mapping Accuracy on Diverse Platforms

Jianhao Jiao, Hexiang Wei, Tianshuai Hu, Xiangcheng Hu, Yilong Zhu, Zhijian He +7

IROS 2022poster

Combining multiple sensors enables a robot to maximize its perceptual awareness of environments and enhance its robustness to external disturbance, crucial to robotic navigation. This paper proposes the FusionPortable benchmark, a complete multi-sensor dataset with a diverse set of sequences for mob…

Cited by 39 Source ↗Scholar ↗