Publication Details

SELECT * FROM publications WHERE Record_Number=10513
Reference TypeConference Proceedings
Author(s)Deisenroth, M.P.; Ohlsson, H.
TitleA General Perspective on Gaussian Filtering and Smoothing: Explaining Current and Deriving new Algorithms
Journal/Conference/Book TitleAmerican Control Conference (ACC 2011)
KeywordsFiltering, smoothing, Bayesian inference, Gibbs filter
AbstractWe present a general probabilistic perspective on Gaussian filtering and smoothing. This allows us to show that common approaches to Gaussian filtering/smoothing can be dis- tinguished solely by their methods of computing/approximating the means and covariances of joint probabilities. This implies that novel filters and smoothers can be derived straightfor- wardly by providing methods for computing these moments. Based on this insight, we derive the cubature Kalman smoother and propose a novel robust filtering and smoothing algorithm based on Gibbs sampling.
Link to PDF


zum Seitenanfang