Socially intelligent robots that understand and respond to human touch

Merel Madeleine Jung

    Research output: ThesisPhD Thesis - Research UT, graduation UT

    165 Downloads (Pure)


    Touch is an important nonverbal form of interpersonal interaction which is used to communicate emotions and other social messages. As interactions with social robots are likely to become more common in the near future these robots should also be able to engage in tactile interaction with humans. Therefore, the aim of the research presented in this dissertation is to work towards socially intelligent robots that can understand and respond to human touch. To become a socially intelligent actor a robot must be able to sense, classify and interpret human touch and respond to this in an appropriate manner. To this end we present work that addresses different parts of this interaction cycle.

    The contributions of this dissertation are the following. We have made a touch gesture dataset available to the research community and have presented benchmark results. Furthermore, we have sparked interest into the new field of social touch recognition by organizing a machine learning challenge and have pinpointed directions for further research. Also, we have exposed potential difficulties for the recognition of social touch in more naturalistic settings. Moreover, the findings presented in this dissertation can help to inform the design of a behavioral model for robot pet companions that can understand and respond to human touch. Additionally, we have focused on the requirements for tactile interaction with robot pets for health care applications.
    Original languageEnglish
    Awarding Institution
    • University of Twente
    • Heylen, Dirk K.J., Supervisor
    • Poel, Mannes, Supervisor
    Award date28 Jun 2017
    Place of PublicationEnschede
    Print ISBNs978-90-365-4364-4
    Publication statusPublished - Jun 2017


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