A knowledge integration framework for robotics

Summary, in English

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.

• Författare: Jacob Persson; Axel Gallois; Anders Björkelund; Love Hafdell; Mathias Haage; Jacek Malec; Klas Nilsson; Pierre Nugues
• Avdelning/ar: ELLIIT: the Linköping-Lund initiative on IT and mobile communication; Institutionen för datavetenskap; Robotik och Semantiska System
• Publiceringsår: 2010
• Språk: Engelska
• 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)
• Dokumenttyp: Konferensbidrag
• Ämne: Computer Science
• Conference name: ISR/Robotik
• Conference date: 2010-06-07 - 2010-06-09
• Conference place: Munich, Germany
• Status: Published
• Forskningsgrupp: RSS
• ISBN/ISSN/Övrigt: ISBN: 978-3-8007-3273-9