Abstract
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.
| Original language | English |
|---|---|
| Title of host publication | 2024 IEEE International Conference on Robotics and Automation, ICRA 2024 |
| Publisher | IEEE |
| Pages | 11906-11912 |
| Number of pages | 7 |
| ISBN (Electronic) | 9798350384574 |
| DOIs | |
| Publication status | Published - 2024 |
| Event | 2024 IEEE International Conference on Robotics and Automation, ICRA 2024 - Yokohama, Japan Duration: 13 May 2024 → 17 May 2024 |
Publication series
| Name | Proceedings - IEEE International Conference on Robotics and Automation |
|---|---|
| ISSN (Print) | 1050-4729 |
Conference
| Conference | 2024 IEEE International Conference on Robotics and Automation, ICRA 2024 |
|---|---|
| Country/Territory | Japan |
| City | Yokohama |
| Period | 13/05/24 → 17/05/24 |
Bibliographical note
Green Open Access added to TU Delft Institutional Repository ‘You share, we take care!’ – Taverne project https://www.openaccess.nl/en/you-share-we-take-careOtherwise as indicated in the copyright section: the publisher is the copyright holder of this work and the author uses the Dutch legislation to make this work public.
Keywords
- Kalman Filter
- Sensor Fusion
- State Estimation