From AutomationML to ROS: A model-driven approach for software engineering of industrial robotics using ontological reasoning

Abstract

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.