Couch to 5km robot coach: An autonomous, human-trained socially assistive robot

Katie Winkle, Séverin Lemaignan, Praminda Caleb-Solly, Ute Leonards, Ailie Turton, Paul Bremner

Research output: Chapter in Book/Report/Conference proceedingConference Contribution (Conference Proceeding)

Abstract

We present a robot exercise coach, co-designed and then trained in real-time by a human fitness instructor, via interactive machine learning, to support the UK National Health Service (NHS) Couch to 5km (C25K) programme. The programme consists of undertaking 3x weekly exercise sessions for 9 weeks, with sessions building up from a combination of short runs and walks to a full 30 minutes running. The simplicity (and relatively boring nature) of the task places great importance on the ability of the robot, our 'C25K coach', to provide engaging and appropriate social supporting behaviour.

Original languageEnglish
Title of host publicationHRI 2020 - Companion of the 2020 ACM/IEEE International Conference on Human-Robot Interaction
PublisherIEEE Computer Society
Pages520-522
Number of pages3
ISBN (Electronic)9781450370578
DOIs
Publication statusPublished - 23 Mar 2020
Event15th Annual ACM/IEEE International Conference on Human Robot Interaction, HRI 2020 - Cambridge, United Kingdom
Duration: 23 Mar 202026 Mar 2020

Publication series

NameACM/IEEE International Conference on Human-Robot Interaction
ISSN (Electronic)2167-2148

Conference

Conference15th Annual ACM/IEEE International Conference on Human Robot Interaction, HRI 2020
CountryUnited Kingdom
CityCambridge
Period23/03/2026/03/20

Keywords

  • Machine learning
  • Participatory design
  • Socially assistive robotics

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    Winkle, K., Lemaignan, S., Caleb-Solly, P., Leonards, U., Turton, A., & Bremner, P. (2020). Couch to 5km robot coach: An autonomous, human-trained socially assistive robot. In HRI 2020 - Companion of the 2020 ACM/IEEE International Conference on Human-Robot Interaction (pp. 520-522). (ACM/IEEE International Conference on Human-Robot Interaction). IEEE Computer Society. https://doi.org/10.1145/3371382.3378337