Pignaton De Freitas, Edison, Olszewska, Joanna Isabelle, Carbonera, Joel Luís, Fiorini, Sandro R., Khamis, Alaa, Ragavan, S. Veera, Barreto, Marcos E. ORCID: 0000-0002-7818-1855, Prestes, Edson, Habib, Maki K., Redfield, Signe, Chibani, Abdelghani, Goncalves, Paulo, Bermejo-Alonso, Julita, Sanz, Ricardo, Tosello, Elisa, Olivares-Alarcos, Alberto, Konzen, Andrea Aparecida, Quintas, João and Li, Howard (2020) Ontological concepts for information sharing in cloud robotics. Journal of Ambient Intelligence and Humanized Computing. ISSN 1868-5137
Text (Barreto_ontologial-concepts-for-information--accepted)
- Accepted Version
Download (1MB) |
Abstract
Recent research and developments in cloud robotics (CR) require appropriate knowledge representation to ensure interoperable data, information, and knowledge sharing within cloud infrastructures. As an important branch of the Internet of Things (IoT), these demands to advance it forward motivates academic and industrial sectors to invest on it. The IEEE ’Ontologies for Robotics and Automation’ Working Group (ORA WG) has been developing standard ontologies for different robotic domains, including industrial and autonomous robots. The use of such robotic standards has the potential to benefit the Cloud Robotic Community (CRC) as well, supporting the provision of ubiquitous intelligent services by the CR-based systems. This paper explores this potential by developing an ontological approach for effective information sharing in cloud robotics scenarios. It presents an extension to the existing ontological standards to cater for the CR domain. The use of the new ontological elements is illustrated through its use in a couple of CR case studies. To the best of our knowledge, this is the first work ever that implements an ontology comprising concepts and axioms applicable to the CR domain.
Item Type: | Article |
---|---|
Official URL: | https://www.springer.com/journal/12652 |
Additional Information: | © 2020 Springer-Verlag GmbH Germany, part of Springer Nature 2 |
Divisions: | Statistics |
Subjects: | Q Science > QA Mathematics > QA75 Electronic computers. Computer science |
Date Deposited: | 03 Aug 2022 08:09 |
Last Modified: | 20 Dec 2024 00:45 |
URI: | http://eprints.lse.ac.uk/id/eprint/115771 |
Actions (login required)
View Item |