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An Extensible Semantic Data Fusion Framework for Autonomous Vehicles

Authors:
Efstratios Kontopoulos
Panagiotis Mitzias
Konstantinos Avgerinakis
Pavlos Kosmides
Nikos Piperigkos
Christos Anagnostopoulos
Aris S. Lalos
Nikolaos Stagakis
Gerasimos Arvanitis
Evangelia I. Zacharaki
Konstantinos Moustakas

Keywords: Autonomous vehicles; ontologies; knowledge graphs; semantic data fusion; AI.

Abstract:
Fully autonomous vehicles may still be an elusive goal, however, research on the deployment of relevant AI 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.

Pages: 5 to 11

Copyright: Copyright (c) IARIA, 2021

Publication date: October 3, 2021

Published in: conference

ISSN: 2308-4510

ISBN: 978-1-61208-888-4

Location: Barcelona, Spain

Dates: from October 3, 2021 to October 7, 2021