One of the major investment for applying industrial robots in production resides in the software development, which is an interdisciplinary and heterogeneous engineering process. This paper presents a novel model-driven approach that uses AutomationML as modeling framework and ontological reasoning as inference framework for constructing robotic application using Robot Operating System (ROS). We show how different robotic components can be classified and modeled with AutomationML, how these components can be composed together to a production system, and how the AutomationML models can be processed semantically by utilizing Semantic Web technologies and ontological reasoning. By applying model-to-text transformation techniques, executable ROS code can be generated from the models that foster fast prototyping and the reuse of robotic software
This paper presents a novel ontology-based approach that uses Description Logics as a knowledge representation framework for the description, aggregation, propagation, and interlinkage of features pertaining to robots and robot-centric workplaces. We show how different classification systems for capabilities and components can be axiomatically linked together, how features can be propagated along compound components, and how complex features can be computed on the basis of combining role inclusion, role composition, and general concept inclusion axioms. In a second use case that is related to the logical deduction of potential hazards for a given workplace configuration, we show that the presented approach is applicable to similar modeling problems
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