A new point-cloud-based LiDAR/IMU localization method with uncertainty evaluation

Ali Hassani, Mathieu Joerger

Research output: Chapter in Book/Report/Conference proceedingConference contribution

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.

Original languageEnglish (US)
Title of host publicationProceedings of the 34th International Technical Meeting of the Satellite Division of the Institute of Navigation, ION GNSS+ 2021
PublisherInstitute of Navigation
Pages636-651
Number of pages16
ISBN (Electronic)9780936406299
DOIs
StatePublished - 2021
Externally publishedYes
Event34th International Technical Meeting of the Satellite Division of the Institute of Navigation, ION GNSS+ 2021 - St. Louis, United States
Duration: Sep 20 2021Sep 24 2021

Publication series

NameProceedings of the 34th International Technical Meeting of the Satellite Division of the Institute of Navigation, ION GNSS+ 2021

Conference

Conference34th International Technical Meeting of the Satellite Division of the Institute of Navigation, ION GNSS+ 2021
Country/TerritoryUnited States
CitySt. Louis
Period9/20/219/24/21

ASJC Scopus subject areas

  • Computer Science Applications
  • Software
  • Electrical and Electronic Engineering

Fingerprint

Dive into the research topics of 'A new point-cloud-based LiDAR/IMU localization method with uncertainty evaluation'. Together they form a unique fingerprint.

Cite this