A knowledge integration framework for robotics
Publikation/Tidskrift/Serie: ISR/ROBOTIK 2010 : proceedings for the joint conference of ISR 2010 (41st International Symposium on Robotics) and ROBOTIK 2010 (6th German Conference on Robotics)
This paper describes a knowledge integration framework for robotics, whose goal is to represent, store, adapt, and distribute knowledge across engineering platforms. The architecture abstracts the components as data sources, where data are available in the AutomationML data exchange format. AutomationML is an on-going standard initiative that aims at unifying data representation and APIs used by engineering tools. A triplification procedure converts native formats used by data sources into RDF triples and then exposes them via a SPARQL endpoint. The triplification step has been implemented for the CAEX top level and logic data parts of AutomationML, where the conversion uses XSLT rules.
- Technology and Engineering
- ISBN: 978-3-8007-3273-9