%0 Journal Article %T Set-membership localization with probabilistic errors %+ Extraction et Exploitation de l'Information en Environnements Incertains (E3I2) %A Jaulin, Luc %Z WOS %< avec comité de lecture %@ 0921-8890 %J Robotics and Autonomous Systems %I Elsevier %V 59 %N 6 %P 489-495 %8 2011-06 %D 2011 %R 10.1016/j.robot.2011.03.005 %K Gaussian noise %K Interval analysis %K Probabilistic estimation %K Robust estimation %K Set-membership estimation %K Outliers %Z Engineering Sciences [physics]/AutomaticJournal articles %X Interval methods have been shown to be efficient, robust and reliable to solve difficult set-membership localization problems. However, they are unsuitable in a probabilistic context, where the approximation of an unbounded probability density function by a set cannot be accepted. This paper proposes a new probabilistic approach which makes possible to use classical set-membership localization methods which are robust with respect to outliers. The approach is illustrated on two simulated examples. %G English %2 https://ensta-bretagne.hal.science/hal-00593265/document %2 https://ensta-bretagne.hal.science/hal-00593265/file/paper_probintk_ras.pdf %L hal-00593265 %U https://ensta-bretagne.hal.science/hal-00593265 %~ ENSTA-BRETAGNE %~ ENSTA-BRETAGNE-STIC %~ ENSIETA-E3I2 %~ TDS-MACS