Invariant Kalman Filtering with Noise-Free Pseudo-Measurements
- Resource Type
- Conference
- Authors
- Goffin, Sven; Bonnabel, Silvere; Bruls, Olivier; Sacre, Pierre
- Source
- 2023 62nd IEEE Conference on Decision and Control (CDC) Decision and Control (CDC), 2023 62nd IEEE Conference on. :8665-8671 Dec, 2023
- Subject
- Computing and Processing
Power, Energy and Industry Applications
Robotics and Control Systems
Wireless communication
Cranes
Uncertainty
Three-dimensional displays
Filtering
Pose estimation
Kalman filters
- Language
- ISSN
- 2576-2370
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.