Saved in:
| Main Authors: | , , , |
|---|---|
| Format: | Preprint |
| Published: |
2024
|
| Subjects: | |
| Online Access: | https://arxiv.org/abs/2404.10687 |
| Tags: |
Add Tag
No Tags, Be the first to tag this record!
|
| _version_ | 1866917641744023552 |
|---|---|
| author | Goffin, Sven Bonnabel, Silvère Brüls, Olivier Sacré, Pierre |
| author_facet | Goffin, Sven Bonnabel, Silvère Brüls, Olivier Sacré, Pierre |
| contents | In this paper, we focus on developing an Invariant Extended Kalman Filter (IEKF) for extended pose estimation for a noisy system with state equality constraints. We treat those constraints as noise-free pseudo-measurements. To this aim, we provide a formula for the Kalman gain in the limit of noise-free measurements and rank-deficient covariance matrix. We relate the constraints to group-theoretic properties and study the behavior of the IEKF in the presence of such noise-free measurements. We illustrate this perspective on the estimation of the motion of the load of an overhead crane, when a wireless inertial measurement unit is mounted on the hook. |
| format | Preprint |
| id |
arxiv_https___arxiv_org_abs_2404_10687 |
| institution | arXiv |
| publishDate | 2024 |
| record_format | arxiv |
| spellingShingle | Invariant Kalman Filtering with Noise-Free Pseudo-Measurements Goffin, Sven Bonnabel, Silvère Brüls, Olivier Sacré, Pierre Systems and Control In this paper, we focus on developing an Invariant Extended Kalman Filter (IEKF) for extended pose estimation for a noisy system with state equality constraints. We treat those constraints as noise-free pseudo-measurements. To this aim, we provide a formula for the Kalman gain in the limit of noise-free measurements and rank-deficient covariance matrix. We relate the constraints to group-theoretic properties and study the behavior of the IEKF in the presence of such noise-free measurements. We illustrate this perspective on the estimation of the motion of the load of an overhead crane, when a wireless inertial measurement unit is mounted on the hook. |
| title | Invariant Kalman Filtering with Noise-Free Pseudo-Measurements |
| topic | Systems and Control |
| url | https://arxiv.org/abs/2404.10687 |