From Real-time Attention Assessment to “With-me-ness” in Human-Robot Interaction

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  • Presented at: 11th ACM/IEEE Conference on Human-Robot Interaction, Christchurch, New Zealand, 2016
  • Published in: Proceedings of the 2016 ACM/IEEE Human-Robot Interaction Conference, p. 157-164
  • Series: ACMIEEE International Conference on Human-Robot Interaction
  • New York: Ieee, 2016

Measuring “how much the human is in the interaction” — the level of engagement — is instrumental in building effective interactive robots. Engagement, however, is a complex, multi-faceted cognitive mechanism that is only indirectly observable. This article formalizes with-me-ness as one of such indirect measures. With-me-ness, a concept borrowed from the field of Computer-Supported Collaborative Learning, measures in a well-defined way to what extent the human is with the robot over the course of an interactive task. As such, it is a meaningful precursor of engagement. We expose in this paper the full methodology, from real-time estimation of the human’s focus of attention (relying on a novel, open-source, vision-based head pose estimator), to on-line computation of with-me-ness. We report as well on the experimental validation of this approach, using a naturalistic setup involving children during a complex robot-teaching task.

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