An Extensible Semantic Data Fusion Framework for Autonomous Vehicles
Efstratios Kontopoulos, Panagiotis Mitzias, Konstantinos Avgerinakis, Pavlos Kosmides, Nikos Piperigkos, Christos B. Anagnostopoulos, Aris S. Lalos, Nikolaos Stagakis, Gerasimos Arvanitis, Evangelia I. Zacharaki, Κωνσταντίνος Μουστάκας · Zenodo (CERN European Organization for Nuclear Research) · 2021
Fully autonomous vehicles may still be an elusive goal, however, research in the deployment of relevant Artificial Intelligence technologies in the domain is rapidly gaining traction. A key challenge lies in the fusion of all the diverse information from the various sensors on the vehicle and its environment. In this context, ontologies and semantic technologies can effectively address this challenge by semantically fusing heterogeneous pieces of information into a uniform Knowledge Graph. This paper presents CASPAR, an extensible semantic data fusion platform for autonomous vehicles. Two use case scenarios are also presented that demonstrate the framework’s versatility.