Knowledge driven robotics for kitting applications

Authors:
Stephen Balakirsky;Zeid Kootbally;Thomas Kramer;Anthony Pietromartire;Craig Schlenoff;Satyandra Gupta
Affiliations:
-;-;-;-;-;-
Venue:
Robotics and Autonomous Systems
Year:
2013

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Ontology-based state representations for intention recognition in human-robot collaborative environments

Robotics and Autonomous Systems

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Abstract

This article presents a newly developed knowledge methodology/model that was designed to support the IEEE Robotics and Automation Society's Ontologies for Robotics and Automation Working Group. This methodology/model allows for the creation of systems that demonstrate flexibility, agility, and the ability to be rapidly re-tasked. The methodology/model will be illustrated through a case study in the area of robotic kit building. Through this case study, the knowledge model will be presented, and automatic tools for optimizing the knowledge representation for planning systems and execution systems will be discussed.