GPS-VIO Fusion with Online Rotational Calibration
Fuente:
arXiv
Saved in:
| Main Authors: | , , , , |
|---|---|
| Format: | Preprint |
| Published: |
2023
|
| Subjects: | |
| Online Access: | |
| Tags: |
Add Tag
No Tags, Be the first to tag this record!
|
| _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 |