A Novel Data Fusion Architecture for Unmanned Vehicles
I. Ermolov
Abstract:
An effective functioning of unmanned vehicles demands to process large amounts of various data coming from sensors, on-board data bases etc. Therefore date fusion technology is one of key-technologies for autonomous vehicles and systems. In order to systemize such data processing special so-called data fusion architectures are used (e.g. JDL, Waterfall, Boyd etc.). However some of those have a list of restrictions w. A goal of this paper is to present a novel data fusion architecture which could be used on board of unmanned vehicles. This architecture consists of 5 basic layers: parameters identification, state identification, (object type identification), situation identification and task implementation identification. The proposed architecture has some advantages in comparison to those already in use. Author considers that presented architecture has good visibility, intuitive understanding, possibility for deep feedback usage and good potenial for automatic reconfiguration and self-learning. The developed data fusion architecture can be used for building complex data fusion systems on board of unmanned vehicles as well as of group of vehicles and even of systems of higher hierarchy.
