Modelling Human Memory in Robotic Companions for Personalisation and Long-term Adaptation in HRI

Authors:
Wan Ching Ho;Kerstin Dautenhahn;Mei Yii Lim;Kyron Du Casse
Affiliations:
Adaptive Systems Research Group, School of Computer Science, University of Hertfordshire, UK;Adaptive Systems Research Group, School of Computer Science, University of Hertfordshire, UK;School of Mathematical and Computer Sciences, Heriot Watt University, UK;Adaptive Systems Research Group, School of Computer Science, University of Hertfordshire, UK
Venue:
Proceedings of the 2010 conference on Biologically Inspired Cognitive Architectures 2010: Proceedings of the First Annual Meeting of the BICA Society
Year:
2010

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Abstract

This paper investigates issues of robot's personalization and long-term adaptation in human-robot interaction (HRI). It demonstrates the design and first technical implementation of a HRI showcase in the Robot House at University of Hertfordshire, UK. Here the central idea facilitating the long-term HRI is the creation of robotic companion, which provides various types of service to the user and can be personalised based upon individual needs. The personalisation can also be further enhanced through repeated interactions. The key component in the “mind” of the companion, which is highlighted in this paper, is the model of human semantic and episodic memory. The memory not only allows the companion to remember user's preferences for practical daily tasks, it also changes companion's behaviour in a longer time scale based on robot's perception of actual user input. Finally, implications of such a memory model in HRI are discussed.