Exactly sparse Gaussian variational inference with application to derivative-free batch nonlinear state estimation

We present a Gaussian variational inference (GVI) technique that can be applied to large-scale nonlinear batch state estimation problems. The main contribution is to show how to fit both the mean and (inverse) covariance of a Gaussian to the posterior efficiently, by exploiting factorization of the...

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Veröffentlicht in:	The International journal of robotics research 2020-11, Vol.39 (13), p.1473-1502
Hauptverfasser:	Barfoot, Timothy D, Forbes, James R, Yoon, David J
Format:	Artikel
Sprache:	eng
Schlagworte:	Covariance matrix Inference Mathematical analysis State estimation
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