Discovering Social Interaction Strategies for Robots from Restricted-Perception Wizard-of-Oz Studies


Best Paper Award on HRI Interaction Design

Pedro Sequeira, Patrícia Alves-Oliveira, Tiago Ribeiro, Eugenio Di Tullio, Sofia Petisca, Francisco S. Melo, Ginevra Castellano, and Ana Paiva

In Proceedings of the 11th ACM/IEEE International Conference on Human-Robot Interaction (HRI), 2016, pp. 197–204. Discovering Social Interaction Strategies for Robots from Restricted-Perception Wizard-of-Oz StudiesDiscovering Social Interaction Strategies for Robots from Restricted-Perception Wizard-of-Oz Studies


Abstract
In this paper we propose a methodology for the creation of social interaction strategies for human-robot interaction based on restricted-perception Wizard-of-Oz studies (WoZ). This novel experimental technique involves restricting the wizard’s perceptions over the environment and the behaviors it controls according to the robot’s inherent perceptual and acting limitations. Within our methodology, the robot’s design lifecycle is divided into three consecutive phases, namely data collection, where we perform interaction studies to extract expert knowledge and interaction data; strategy extraction, where a hybrid strategy controller for the robot is learned based on the gathered data; strategy refinement, where the controller is iteratively evaluated and adjusted. We developed a fully-autonomous robotic tutor based on the proposed approach in the context of a collaborative learning scenario. The results of the evaluation study show that, by performing restricted-perception WoZ studies, our robots are able to engage in very natural and socially-aware interactions.

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