An Approach to Ontology-based Intention Recognition using State Representations

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.