Social robots have the potential to provide support in a number of practical domains, such as learning and behaviour change. This potential is particularly relevant for children, who have proven receptive to interactions with social robots. To reach learning and therapeutic goals, a number of issues need to be investigated, notably the design of an effective child-robot interaction (cHRI) to ensure the child remains engaged in the relationship and that educational goals are met. Typically, current cHRI research experiments focus on a single type of interaction activity (e.g. a game). However, these can suffer from a lack of adaptation to the child, or from an increasingly repetitive nature of the activity and interaction. In this paper, we motivate and propose a practicable solution to this issue: an adaptive robot able to switch between multiple activities within single interactions. We describe a system that embodies this idea, and present a case study in which diabetic children collaboratively learn with the robot about various aspects of managing their condition. We demonstrate the ability of our system to induce a varied interaction and show the potential of this approach both as an educational tool and as a research method for long-term cHRI.
Towards Long-Term Social Child-Robot Interaction: Using Multi-Activity Switching to Engage Young Users
Michael A. Goodrich - Managing Editor - Brigham Young University, Provo, Utah 84602, Stati Uniti, Stati Uniti d'America
Journal of Human-Robot Interaction 5 (2016). doi:10.5898/JHRI.5.1.Coninx
info:cnr-pdr/source/autori:Alexandre Coninx, Paul Baxter, Elettra Oleari, Sara Bellini, Bert Bierman, Olivier Blanson Henkemans, Lola Cañamero, Piero Cosi, Valentin Enescu, Raquel Ros Espinoza, Antoine Hiolle, Rémi Humbert, Bernd Kiefer, Ivana Kruijff-Kor