Decision-theoretic approach to robust fusion of location data

The purpose of this paper is to introduce the reader to a novel approach to data fusion. We focus on the latest results which have immediate practical implications. Many tasks in active perception require the ability to combi ne information from a variety of sensors. Prior to combination, the data mu st be tested for consistency. Both of these tasks can be viewed as data Fus ion problems. We examine such problems for location data models. Our approa ch is based on statistical decision theory. We present the application of t he theory to mobile robot localization. (C) 1998 The Franklin Institute. Pu blished by Elsevier Science Ltd.