Patricc: A Platform for Triadic Interaction with Changeable Characters

While social robots for education are slowly being integrated in many scenarios, ranging from higher-education, through elementary school and kindergarten, the use case of robots for toddlers in their homes has not gained much attention. In this contribution, we introduce Patricc, a robotic platform that is specifically designed for toddler-parent-robot triadic interaction. It addresses the unique challenges of this age group, namely, desire for continuous physical interaction and novelty. Patricc’s unique design enables changing characters by using dress-able puppets over a 3D-printed skeleton and the use of physical props. A novel authoring tool enables robot behavior and content creation by non-programmers. We conducted an evaluation study with 18 parent-toddler pairs and compared Patricc to similar tablet-based interactions. Our quantitative and qualitative analyses show that Patricc promotes significantly more triadic interaction, measured by video-coded gaze, compared to the tablet and that parents indeed perceive the interaction as triadic. Furthermore, there was no novelty-induced significant change in task-oriented behaviors, when toddlers interacted with two different characters consecutively. Finally, parents pointed out the benefits of changeable puppet-like characters over tablets and the appropriateness of the platform for the target age-group. These results suggest that Patricc can serve as the first gateway of toddlers to the emerging world of social robots. CCS CONCEPTS • Human-centered computing → Empirical studies in HCI; • Applied computing → Interactive learning environments; •Computer systems organization → Robotic autonomy. Acm Reference Format: Omer Gvirsman, Yaacov Koren, Tal Norman, and Goren Gordon. 2020. Patricc: A Platform for Triadic Interaction with Changeable Characters. In Proceedings of the 2020 ACM/IEEE International Conference on HumanRobot Interaction (HRI ’20), March 23–26, 2020, Cambridge, United Kingdom. ACM, New York, NY, USA, 9 pages. https://doi.org/10.1145/3319502.3374792