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Open AccessArticle

A Rule-Based Reasoner for Underwater Robots Using OWL and SWRL

Departamento de Ingeniería Telemática y Electrónica (DTE), Escuela Técnica Superior de Ingeniería y Sistemas de Telecomunicación (ETSIST), Universidad Politécnica de Madrid (UPM), C/Nikola Tesla, s/n, 28031 Madrid, Spain
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Sensors 2018, 18(10), 3481; https://doi.org/10.3390/s18103481
Received: 13 August 2018 / Revised: 27 September 2018 / Accepted: 10 October 2018 / Published: 16 October 2018
(This article belongs to the Special Issue Underwater Sensor Networks: Applications, Advances and Challenges)
Web Ontology Language (OWL) is designed to represent varied knowledge about things and the relationships of things. It is widely used to express complex models and address information heterogeneity of specific domains, such as underwater environments and robots. With the help of OWL, heterogeneous underwater robots are able to cooperate with each other by exchanging information with the same meaning and robot operators can organize the coordination easier. However, OWL has expressivity limitations on representing general rules, especially the statement “If … Then … Else …”. Fortunately, the Semantic Web Rule Language (SWRL) has strong rule representation capabilities. In this paper, we propose a rule-based reasoner for inferring and providing query services based on OWL and SWRL. SWRL rules are directly inserted into the ontologies by several steps of model transformations instead of using a specific editor. In the verification experiments, the SWRL rules were successfully and efficiently inserted into the OWL-based ontologies, obtaining completely correct query results. This rule-based reasoner is a promising approach to increase the inference capability of ontology-based models and it achieves significant contributions when semantic queries are done. View Full-Text
Keywords: underwater robots; semantic representation; ontology languages; SWRL rules; rule-based reasoning underwater robots; semantic representation; ontology languages; SWRL rules; rule-based reasoning
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Zhai, Z.; Martínez Ortega, J.-F.; Lucas Martínez, N.; Castillejo, P. A Rule-Based Reasoner for Underwater Robots Using OWL and SWRL. Sensors 2018, 18, 3481.

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