An approach to ontology-based intention recognition using state representations

Craig Schlenoff, S. Foufou, S. Balakirsky

Research output: Chapter in Book/Report/Conference proceedingConference contribution

Abstract

In this paper, we present initial thoughts on an approach to ontology/logic-based intention recognition based on the recognition, representation, and ordering of states. This is different than traditional approaches to intention recognition, which use activity recognition and the ordering of activities. State recognition and representation offer numerous advantages, including the ability to infer the intention of multiple people working together and the fact that states are easier for a sensor system to recognize than actions. The focus of this work is on the domain of manufacturing assembly, with an emphasis on human/robot collaboration during the assembly process.

Original languageEnglish (US)
Title of host publicationKEOD 2012 - Proceedings of the International Conference on Knowledge Engineering and Ontology Development
Pages178-183
Number of pages6
StatePublished - Dec 1 2012
Event4th International Conference on Knowledge Engineering and Ontology Development, KEOD 2012 - Barcelona, Spain
Duration: Oct 4 2012Oct 7 2012

Publication series

NameKEOD 2012 - Proceedings of the International Conference on Knowledge Engineering and Ontology Development

Other

Other4th International Conference on Knowledge Engineering and Ontology Development, KEOD 2012
CountrySpain
CityBarcelona
Period10/4/1210/7/12

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Keywords

  • Human-robot interaction and safety
  • Intention recognition
  • Ontology
  • State representation

ASJC Scopus subject areas

  • Information Systems
  • Software

Cite this

Schlenoff, C., Foufou, S., & Balakirsky, S. (2012). An approach to ontology-based intention recognition using state representations. In KEOD 2012 - Proceedings of the International Conference on Knowledge Engineering and Ontology Development (pp. 178-183). (KEOD 2012 - Proceedings of the International Conference on Knowledge Engineering and Ontology Development).