AAAI Publications, 2010 AAAI Fall Symposium Series

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Joint Attention in Human-Robot Interaction
Chien-Ming Huang, Andrea L. Thomaz

Last modified: 2010-11-03


We propose a computational model of joint attention consisting of three parts: responding to joint attention, initiating joint attention, and ensuring joint attention. This model is supported by psychological findings and matches the developmental timeline in humans. We present two experiments that test this model and investigate joint attention in human-robot interaction. The first experiment explored the effects of responding to joint attention on human-robot interaction. We show that robots responding to joint attention are more transparent to humans and are more competent and socially interactive. The second experiment studied the importance of ensuring joint attention in human-robot interaction. Data upheld our hypotheses that a robot's ensuring joint attention behavior yields better performance in human-robot interactive tasks and ensuring joint attention behaviors are perceived as natural behaviors.


Joint Attention; Human-Robot Interaction

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