A Knowledge Integration Framework for Robotics
Jacob Persson, Axel Gallois, Anders J. Björkelund, Love Hafdell, Mathias Haage, Jacek Malec, Klas Nilsson, Pierre Nugues · 2010
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. 1