GPS-VIO Fusion with Online Rotational Calibration

Fuente: arXiv
Gespeichert in:
Bibliographische Detailangaben
Hauptverfasser: Song, Junlin, Sanchez-Cuevas, Pedro J., Richard, Antoine, Rajan, Raj Thilak, Olivares-Mendez, Miguel
Format: Preprint
Veröffentlicht: 2023
Schlagworte:
Online-Zugang:
Tags: Tag hinzufügen
Keine Tags, Fügen Sie den ersten Tag hinzu!
_version_ 1866917603357753344
author Song, Junlin
Sanchez-Cuevas, Pedro J.
Richard, Antoine
Rajan, Raj Thilak
Olivares-Mendez, Miguel
author_facet Song, Junlin
Sanchez-Cuevas, Pedro J.
Richard, Antoine
Rajan, Raj Thilak
Olivares-Mendez, Miguel
contents Accurate global localization is crucial for autonomous navigation and planning. To this end, various GPS-aided Visual-Inertial Odometry (GPS-VIO) fusion algorithms are proposed in the literature. This paper presents a novel GPS-VIO system that is able to significantly benefit from the online calibration of the rotational extrinsic parameter between the GPS reference frame and the VIO reference frame. The behind reason is this parameter is observable. This paper provides novel proof through nonlinear observability analysis. We also evaluate the proposed algorithm extensively on diverse platforms, including flying UAV and driving vehicle. The experimental results support the observability analysis and show increased localization accuracy in comparison to state-of-the-art (SOTA) tightly-coupled algorithms.
format Preprint
id arxiv_https___arxiv_org_abs_2309_12005
institution arXiv
publishDate 2023
record_format arxiv
spellingShingle GPS-VIO Fusion with Online Rotational Calibration
Song, Junlin
Sanchez-Cuevas, Pedro J.
Richard, Antoine
Rajan, Raj Thilak
Olivares-Mendez, Miguel
Robotics
Accurate global localization is crucial for autonomous navigation and planning. To this end, various GPS-aided Visual-Inertial Odometry (GPS-VIO) fusion algorithms are proposed in the literature. This paper presents a novel GPS-VIO system that is able to significantly benefit from the online calibration of the rotational extrinsic parameter between the GPS reference frame and the VIO reference frame. The behind reason is this parameter is observable. This paper provides novel proof through nonlinear observability analysis. We also evaluate the proposed algorithm extensively on diverse platforms, including flying UAV and driving vehicle. The experimental results support the observability analysis and show increased localization accuracy in comparison to state-of-the-art (SOTA) tightly-coupled algorithms.
title GPS-VIO Fusion with Online Rotational Calibration
topic Robotics
url https://arxiv.org/abs/2309.12005