RDF-Based Semantic for Condition Monitoring of Autonomous Mobile Robot

Abstract

In Industry 4.0 Resource Description Framework (RDF), a semantic data model can be used to solve challenges such as unique identification, data availability, and interoperability. In this study, an integration of environmental, mechanical, and software errors in a common language is proposed for an Autonomous Mobile Robot (AMR) application targeting advancement of autonomy, which is one of the important components in Industry 4.0. For this purpose, a semantic ontology for knowledge-based state monitoring is presented. The proposed approach addresses interoperable communication for condition monitoring using semantic technologies. A common fault tracking system has been developed by creating a dictionary for three different types of faults received using RDF. To the best of our knowledge, this study is the first where an RDF-based representation for a Condition-based monitoring use-case utilizing autonomous robots are proposed and demonstrated.