Human-Robot Interactive Learning Architecture using Ontologies and Symbol Manipulation

Abstract

Robotic systems developed for support can provide assistance in various ways. However, regardless of the service provided, the quality of user interaction is key to adoption by the general public. Simple communication difficulties, such as terminological differences, can make or break the acceptance of robots. In this work we take into account these difficulties in communication between a human and a robot. We propose a system that allows to handle unknown concepts through symbol manipulation based on natural language interactions. In addition, ontologies are used as a convenient way to store the knowledge and reason about it. To demonstrate the use of our system, two scenarios are described and tested with a Care-O-Bot 4. The experiments show that confusions and difficulties in communication can effectively be resolved through symbol manipulation.