Set-membership localization with probabilistic errors

Luc Jaulin (1)

1 E3I2 - Extraction et Exploitation de l'Information en Environnements Incertains

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.

Mots clés: Gaussian noise; Interval analysis; Probabilistic estimation; Robust estimation; Set-membership estimation; Outliers

Domaines: Automatique / Robotique

Luc Jaulin. Set-membership localization with probabilistic errors. Robotics and Autonomous Systems, 2011, 59 (6), pp.489-495. ⟨10.1016/j.robot.2011.03.005⟩. ⟨hal-00593265⟩