‘Teach Me - Show Me’- End-user personalisation of a smart home and companion robot

Joe Saunders, D.S. Syrdal, Kheng Koay, Nathan Burke, K. Dautenhahn

Research output: Contribution to journalArticlepeer-review

46 Citations (Scopus)
226 Downloads (Pure)

Abstract

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.
Original languageEnglish
Pages (from-to)29-40
JournalIEEE Transactions on Human-Machine Systems
Volume46
Issue number1
Early online date9 Nov 2015
DOIs
Publication statusPublished - 1 Feb 2016

Keywords

  • Robot personalisation
  • robot teaching
  • robot learning
  • activity recognition
  • robot companion

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