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Found 7 papers, 4 papers with code
Invariant Kalman Filtering with Noise-Free Pseudo-Measurements
We relate the constraints to group-theoretic properties and study the behavior of the IEKF in the presence of such noise-free measurements.
Variational Gaussian approximation of the Kushner optimal filter
The solution to this last proximal loss is given by implicit updates on the mean and covariance that we proposed earlier.
Variational inference via Wasserstein gradient flows
Along with Markov chain Monte Carlo (MCMC) methods, variational inference (VI) has emerged as a central computational approach to large-scale Bayesian inference.
Associating Uncertainty to Extended Poses for on Lie Group IMU Preintegration with Rotating Earth
The recently introduced matrix group SE2(3) provides a 5x5 matrix representation for the orientation, velocity and position of an object in the 3-D space, a triplet we call ''extended pose''.
Robotics
AI-IMU Dead-Reckoning
In this paper we propose a novel accurate method for dead-reckoning of wheeled vehicles based only on an Inertial Measurement Unit (IMU).
On the Covariance of ICP-based Scan-matching Techniques
This paper considers the problem of estimating the covariance of roto-translations computed by the Iterative Closest Point (ICP) algorithm.
The invariant extended Kalman filter as a stable observer
We analyze the convergence aspects of the invariant extended Kalman filter (IEKF), when the latter is used as a deterministic non-linear observer on Lie groups, for continuous-time systems with discrete observations.
Systems and Control
