@inproceedings{b73044eae9764cce992b934e142e210e,
title = "A new point-cloud-based LiDAR/IMU localization method with uncertainty evaluation",
abstract = "This paper describes the design, analysis, and experimental evaluation of a new spherical-grid-based (SGB) localization algorithm. This method combines a light detection and ranging (LiDAR)'s spherically-parametrized point cloud with measurements from an inertial measurement units (IMU) to estimate the position and orientation of a moving vehicle. It also quantifies navigation uncertainty. This grid-based method does not require feature extraction and data association, which are necessary steps in landmark-based localization. In addition, we developed an automated testbed to analyze the probabilistic performance of a landmark-based method and of the new spherical grid-based algorithm. The sample and analytical error distributions for both methods are evaluated in a lab environment.",
author = "Ali Hassani and Mathieu Joerger",
note = "Publisher Copyright: {\textcopyright} 2021 Proceedings of the 34th International Technical Meeting of the Satellite Division of the Institute of Navigation, ION GNSS+ 2021. All rights reserved.; 34th International Technical Meeting of the Satellite Division of the Institute of Navigation, ION GNSS+ 2021 ; Conference date: 20-09-2021 Through 24-09-2021",
year = "2021",
doi = "10.33012/2021.17905",
language = "English (US)",
series = "Proceedings of the 34th International Technical Meeting of the Satellite Division of the Institute of Navigation, ION GNSS+ 2021",
publisher = "Institute of Navigation",
pages = "636--651",
booktitle = "Proceedings of the 34th International Technical Meeting of the Satellite Division of the Institute of Navigation, ION GNSS+ 2021",
address = "United States",
}