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Original languageEnglish
Pages (from-to)29-40
JournalIEEE Transactions on Human-Machine Systems
Journal publication date1 Feb 2016
Early online date9 Nov 2015
StatePublished - 1 Feb 2016


Care issues and costs associated with an increasing elderly population is becoming a major concern for many countries. The use of assistive robots in ‘smart-home’ environments has been suggested as a possible partial solution to these concerns. One of the many challenges faced is the personalisation of the robot to meet the changing needs of the elderly person over time. One approach is to allow the elderly person, or their
carers or relatives, to teach the robot to both recognise activities in the smart home and to teach it to carry out behaviours in response to these activities. The overriding premise being that such teaching is both intuitive and ‘non-technical’. As part of a European project researching and evaluating these issues a commercially available autonomous robot has been deployed in a fully sensorised but otherwise ordinary suburban house.
Occupants of the house are equipped with a non-technical teaching and learning system. This paper details the design approach to the teaching, learning, robot and smart home systems as an integrated unit and presents results from an evaluation of the teaching component and a preliminary evaluation of the learning component in a Human-Robot interaction experiment. Results from this evaluation indicated that participants overall found this approach to personalisation useful, easy to use, and felt that they would be capable of using it in a real-life situation
both for themselves and for others. However there were also some salient individual differences within the sample.


This is the accepted manuscript version of the following article: J. Saunders, D S Syrdal, K L Koay, N Burke and K Dautenhahn, Senior Member, IEEEE, '"Teach Me-Show Me" - End-User Pesonalization of a Smart Home and Companion Robot', IEEE Transactions on Human-Machine Systems, Vol 46(1), first published online November 9, 2015. the version of record is available online at doi: 10.1109/THMS.2015.2445105 (c) 2015 IEEE. Personal use of this material is permitted. Permission from IEEE must be obtained for all other users, including reprinting/ republishing this material for advertising or promotional purposes, creating new collective works for resale or redistribution to servers or lists, or reuse of any copyrighted components of this work in other works

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