In this paper, we investigate the impact the contingency of robot feedback may have on the quality of verbal human-robot interaction. In order to assess not only what the effects are but also what they are caused by, we carried out experiments in which naïve participants instructed the humanoid robot iCub on a set of shapes and on a stacking task in two conditions, once with socially contingent, nonverbal feedback implemented in response to different gaze and looming behaviors of the human tutor, and once with non-contingent, saliency-based feedback. The results of the analysis of participants’ linguistic behaviors in the two conditions show that contingency has an impact on the complexity and the pre-structuring of the task for the robot, i.e. on the participants’ tutoring behaviors. Contingency thus plays a considerable role for learning by demonstration.
Collaboration Technologies and Systems (cts), 2013 International Conference on, 2013, p. 210-217
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4th International Workshop on Collaborative Robots and Human Robot Interaction, 2013