A New Estimation Method for Multisensor Fusion by using Interval Analysis and Particle Filtering

Abstract

This paper presents a new fusion strategy that mixes interval analysis techniques and particle filters for data fusion and state estimation purposes occurring in many robotic perception problems. The method requires a small number of "box particles". This, in fact, answers one of major problems when using particle filters techniques. We report the case study of a land vehicle localization problem and we make a comparison based on real data between the performance of a particle filter and the new developed strategy.