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

Hua, Yingbing; Zander, Stefan; Bordignon, Mirko; Hein, Björn

doi:10.1109/etfa.2016.7733579

Cited by 27 publications

(15 citation statements)

References 15 publications

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“…Some research effort was spent on the combination of Au-tomationML and ontologies, in order to generate automation solutions based on the robot operating system (ROS) [8]. In [9], the authors investigate the analogies between Au-tomationML and OPC UA information models, with the aim of AutomationML data assisting in the design of OPC UA information models.…”

Section: Related Workmentioning

confidence: 99%

OPC UA NodeSet Ontologies as a Pillar of Representing Semantic Digital Twins of Manufacturing Resources

Perzylo

Profanter

Rickert

et al. 2019

2019 24th IEEE International Conference on Emerging Technologies and Factory Automation (ETFA)

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The effectiveness of cognitive manufacturing systems in agile production environments heavily depends on the automatic assessment of various levels of interoperability between manufacturing resources. For taking informed decisions, a semantically rich representation of all resources in a workcell or production line is required. OPC UA provides means for communication and information exchange in such distributed settings. This paper proposes a semantic representation of a resource's properties, in which we use OWL ontologies to encode the information models that can be found in OPC UA NodeSet specifications. We further combine these models with an OWLbased description of the resource's geometry and-if applicable-its kinematic model. This leads to a comprehensive semantic representation of hardware and software features of a manufacturing resource, which we call semantic digital twin. Among other things, it reduces costs through virtual prototyping and enables the automatic deployment of manufacturing tasks in production lines. As a result, small-batch assemblies become financially viable. In order to minimize the effort of creating OWL-based UA NodeSet descriptions, we provide a software tool for the automatic transformation of XML-based NodeSet specifications that adhere to the OPC Foundation's NodeSet2 XML schema.

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Section: Related Workmentioning

confidence: 99%

OPC UA NodeSet Ontologies as a Pillar of Representing Semantic Digital Twins of Manufacturing Resources

Perzylo

Profanter

Rickert

et al. 2019

2019 24th IEEE International Conference on Emerging Technologies and Factory Automation (ETFA)

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“…To demonstrate the use cases of the proposed approach, we discuss two typical scenarios in ontology engineering ( Figure 5). For editing AML models, we recommend the AML editor 4 . In the first use case (orange arrows in Figure 5), the required OWL class does not exist yet, and a user wants to create an AML concept model for the concept in mind:…”

Section: Use Casesmentioning

confidence: 99%

“…For example, with predefined ontological descriptions about error types in plant models, Abele et al were able to identify modeling errors in the plant topology [3]. Hua et al proposed a model-driven robot programming approach that is capable of inferring component capability and the associated programming interfaces from AML models [4]. In this paper, we use the term AML ontology to indicate an OWL ontology that is converted from an AML document.…”

Section: Introductionmentioning

confidence: 99%

Interpreting OWL Complex Classes in AutomationML based on Bidirectional Translation

Hua

Hein

2019

2019 24th IEEE International Conference on Emerging Technologies and Factory Automation (ETFA)

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The World Wide Web Consortium (W3C) has published several recommendations for building and storing ontologies, including the most recent OWL 2 Web Ontology Language (OWL). These initiatives have been followed by practical implementations that popularize OWL in various domains. For example, OWL has been used for conceptual modeling in industrial engineering, and its reasoning facilities are used to provide a wealth of services, e.g. model diagnosis, automated code generation, and semantic integration. More specifically, recent studies have shown that OWL is well suited for harmonizing information of engineering tools stored as AutomationML (AML) files. However, OWL and its tools can be cumbersome for direct use by engineers such that an ontology expert is often required in practice. Although much attention has been paid in the literature to overcome this issue by transforming OWL ontologies from/to AML models automatically, dealing with OWL complex classes remains an open research question. In this paper, we introduce the AML concept models for representing OWL complex classes in AutomationML, and present algorithms for the bidirectional translation between OWL complex classes and their corresponding AML concept models. We show that this approach provides an efficient and intuitive interface for nonexperts to visualize, modify, and create OWL complex classes.

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“…To this end, a meta-model and a source model are required. A way to apply ontology engineering to the MDE approach is discussed in [31]. In this work, a meta-model is considered as an ontology (TBox) and a source model as an instance of the ontology (ABox).…”

Section: Ems-ontology Exploited By the Mde Approachmentioning

confidence: 99%

Engineering Support for Handling Controller Conflicts in Energy Storage Systems Applications

et al. 2017

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Abstract:Energy storage systems will play a major role in the decarbonization of future sustainable electric power systems, allowing a high penetration of distributed renewable energy sources and contributing to the distribution network stability and reliability. To accomplish this, a storage system is required to provide multiple services such as self-consumption, grid support, peak-shaving, etc. The simultaneous activation of controllers operation may lead to conflicts, as a consequence the execution of committed services is not guaranteed. This paper presents and discusses a solution to the exposed issue by developing an engineering support approach to semi-automatically detect and handle conflicts for multi-usage storage systems applications. To accomplish that an ontology is developed and exploited by model-driven engineering mechanisms. The proposed approach is evaluated by implementing a use case example, where detection of conflicts is automatically done at an early design stage. Besides this, exploitable source code for conflicts resolution is generated and used during the design and prototype stages of controllers development. Thus, the proposed engineering support enhances the design and development of storage system controllers, especially for multi-usage applications.

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

Cited by 27 publications

References 15 publications

OPC UA NodeSet Ontologies as a Pillar of Representing Semantic Digital Twins of Manufacturing Resources

OPC UA NodeSet Ontologies as a Pillar of Representing Semantic Digital Twins of Manufacturing Resources

Interpreting OWL Complex Classes in AutomationML based on Bidirectional Translation

Engineering Support for Handling Controller Conflicts in Energy Storage Systems Applications

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