Robust probabilistic positioning based on high-level sensor-fusion and map knowledge

Abstract

Location information as a piece of context is considered to be of particular interest to ubiquitous computing applications. In this work, we present a probabilistic positioning service that employs an available ubiquitous computing infrastructure for the localization of mobile devices. The service draws on various heterogeneous sensors that serve as sources of location information. Data from these sources are transformed independently of each other into an abstract representation of location estimates. By means of a probabilistic fusion process, these estimates are then combined into a single position value. The quality of the result increases with the number of available sensors. Also, since the fusion procedure is not depending on the type and number of available sensors, failures of single sensors or sensor types can be tolerated.