Publication Details

SELECT * FROM publications WHERE Record_Number=10510
Reference TypeJournal Article
Author(s)Deisenroth, M.P.; Turner, R.; Huber, M.; Hanebeck, U.D.; Rasmussen, C.E
TitleRobust Filtering and Smoothing with Gaussian Processes
Journal/Conference/Book TitleIEEE Transactions on Automatic Control
KeywordsGaussian process, filtering, smoothing
AbstractWe propose a principled algorithm for robust Bayesian filtering and smoothing in nonlinear stochastic dynamic systems when both the transition function and the measurement function are described by non-parametric Gaussian process (GP) models. GPs are gaining increasing importance in signal processing, machine learning, robotics, and control for representing unknown system functions by posterior probability distributions. This modern way of "system identification" is more robust than finding point estimates of a parametric function representation. Our principled filteringslash smoothing approach for GP dynamic systems is based on analytic moment matching in the context of the forward-backward algorithm. Our numerical evaluations demonstrate the robustness of the proposed approach in situations where other state-of-the-art Gaussian filters and smoothers can fail.
Number of VolumesIEEE


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