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Publication Citation: An Approach to Ontology-Based Intention Recognition Using State Representations

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Author(s): Craig I. Schlenoff; Sebti Foufou; Stephen B. Balakirsky;
Title: An Approach to Ontology-Based Intention Recognition Using State Representations
Published: October 07, 2012
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.
Proceedings: 4th International Conference on Knowledge Engineering and Ontology Development (KEOD 2012)
Pages: 7 pp.
Location: Barcelona, -1
Dates: October 4-7, 2012
Keywords: intention recognition, human-robot interaction and safety, state representation, ontology
Research Areas: Performance Metrics, Robotics, Ontologies, Process Improvement, Manufacturing
PDF version: PDF Document Click here to retrieve PDF version of paper (880KB)