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Directing Attention Through Gaze Hints Improves Task Solving in Human-Humanoid Interaction.
International Journal of Social Robotics ( IF 3.8 ) Pub Date : 2018-04-06 , DOI: 10.1007/s12369-018-0473-8
Eunice Mwangi 1 , Emilia I Barakova 1 , Marta Díaz-Boladeras 2 , Andreu Català Mallofré 2 , Matthias Rauterberg 1
Affiliation  

In this paper, we report an experimental study designed to examine how participants perceive and interpret social hints from gaze exhibited by either a robot or a human tutor when carrying out a matching task. The underlying notion is that knowing where an agent is looking at provides cues that can direct attention to an object of interest during the activity. In this regard, we asked human participants to play a card matching game in the presence of either a human or a robotic tutor under two conditions. In one case, the tutor gave hints to help the participant find the matching cards by gazing toward the correct match, in the other case, the tutor only looked at the participants and did not give them any help. The performance was measured based on the time and the number of tries taken to complete the game. Results show that gaze hints (helping tutor) made the matching task significantly easier (fewer tries) with the robot tutor. Furthermore, we found out that the robots’ gaze hints were recognized significantly more often than the human tutor gaze hints, and consequently, the participants performed significantly better with the robot tutor. The reported study provides new findings towards the use of non-verbal gaze hints in human–robot interaction, and lays out new design implications, especially for robot-based educative interventions.

中文翻译:

通过注视提示引导注意力可以改善人与人形互动中的任务解决。

在本文中,我们报告了一项实验研究,旨在研究参与者在执行匹配任务时如何从机器人或家庭教师展示的凝视中感知和解释社交提示。基本概念是,知道代理在哪里查看可提供线索,从而可以在活动期间将注意力引向感兴趣的对象。在这方面,我们要求人类参与者在两种情况下在人类或机器人导师在场的情况下玩纸牌配对游戏。在一种情况下,辅导员给出了提示,帮助他们通过凝视正确的比赛来帮助参与者找到匹配的卡片,在另一种情况下,辅导员只看了参与者却没有给予任何帮助。根据完成游戏所需的时间和尝试次数来衡量性能。结果显示,凝视提示(帮助导师)使机器人导师大大简化了匹配任务(减少了尝试)。此外,我们发现,机器人的凝视提示比人类导师的凝视提示更容易识别,因此,参与者在机器人导师中的表现明显更好。报告的研究为在人机交互中使用非语言注视提示提供了新的发现,并提出了新的设计含义,尤其是对基于机器人的教育干预。
更新日期:2018-04-06
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