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A review and comparison of ontology-based approaches to robot autonomy

Published online by Cambridge University Press:  27 December 2019

Alberto Olivares-Alarcos
Affiliation:
Institut de Robòtica i Informàtica Industrial, CSIC-UPC Llorens i Artigas 4-6, 08028Barcelona, Spain e-mail: aolivares@iri.upc.edu
Daniel Beßler
Affiliation:
Institute for Artificial Intelligence, University of Bremen, Germany e-mail: danielb@uni-bremen.de
Alaa Khamis
Affiliation:
Centre for Pattern Analysis and Machine Intelligence, University of Waterloo, Canada
Paulo Goncalves
Affiliation:
IDMEC, Instituto Politécnico de Castelo Branco, Portugal
Maki K. Habib
Affiliation:
The American University in Cairo, Egypt
Julita Bermejo-Alonso
Affiliation:
Universidad Isabel I, Burgos, Spain
Marcos Barreto
Affiliation:
Computer Science Dept., Federal University of Bahia, Brazil
Mohammed Diab
Affiliation:
Institute of Industrial and Control Engineering, Universitat Politècnica de Catalunya, Barcelona, Spain
Jan Rosell
Affiliation:
Institute of Industrial and Control Engineering, Universitat Politècnica de Catalunya, Barcelona, Spain
João Quintas
Affiliation:
Instituto Pedro Nunes, 3030-199Coimbra, Portugal
Joanna Olszewska
Affiliation:
University of the West of Scotland, UK
Hirenkumar Nakawala
Affiliation:
Department of Computer Science, University of Verona, Italy
Edison Pignaton
Affiliation:
Informatics Institute, Federal University of Rio Grande do Sul, Brazil
Amelie Gyrard
Affiliation:
Knoesis, Wright State University, USA
Stefano Borgo
Affiliation:
Laboratory of Applied Ontology ISTC-CNR, Trento, Italy
Guillem Alenyà
Affiliation:
Institut de Robòtica i Informàtica Industrial, CSIC-UPC Llorens i Artigas 4-6, 08028Barcelona, Spain e-mail: aolivares@iri.upc.edu
Michael Beetz
Affiliation:
Institute for Artificial Intelligence, University of Bremen, Germany e-mail: danielb@uni-bremen.de
Howard Li
Affiliation:
University of New Brunswick, Canada

Abstract

Within the next decades, robots will need to be able to execute a large variety of tasks autonomously in a large variety of environments. To relax the resulting programming effort, a knowledge-enabled approach to robot programming can be adopted to organize information in re-usable knowledge pieces. However, for the ease of reuse, there needs to be an agreement on the meaning of terms. A common approach is to represent these terms using ontology languages that conceptualize the respective domain. In this work, we will review projects that use ontologies to support robot autonomy. We will systematically search for projects that fulfill a set of inclusion criteria and compare them with each other with respect to the scope of their ontology, what types of cognitive capabilities are supported by the use of ontologies, and which is their application domain.

Type
Review
Copyright
© Cambridge University Press 2019

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Footnotes

*

Both authors contributed equally to this manuscript

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