Uncertainty and Imprecision Modeling for the Mobile Robot Localization Problem

Abstract

This article deals about uncertainty and imprecision treatment during the mobile robot localization process. The imprecision determination is based on the use of the interval formalism. The mobile robot is equipped with an exteroceptive sensor and odometers. The imprecise data given by these two sensors are fused by constraint propagation on intervals. At the end of the algorithm, we get 3D localization subpaving which is supposed to contain in a guaranteed way the robot’s position. Concerning the uncertainty, it is managed throw a propagation architecture based on the used of the Transferable Belief Model of Smets.