Let Me Tell You! : Investigating the Effects of Robot Communication Strategies in Advice-giving Situations based on Robot Appearance, Interaction Modality and Distance
Let Me Tell You! : Investigating the Effects of Robot Communication Strategies in Advice-giving Situations based on Robot Appearance, Interaction Modality and Distance
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让我告诉你！
DOI：
10.1145/2559636.2559670
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发表时间：
2014
期刊：
影响因子：
--
通讯作者：
Matthias Scheutz
中科院分区：
文献类型：
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作者：
M. Strait;C. Canning;Matthias Scheutz
最近关于机器人在提供建议时应如何与人交谈的提议表明，人类彼此之间采用的策略对机器人同样有效。然而，证据完全基于人们对机器人给其他人提供建议的观察。因此，当人们实际参与与机器人的真实互动时，这些结果是否仍然适用并不明确。我们在一项新颖的系统性混合方法研究中解决了这一缺陷，在该研究中我们采用了基于调查的主观测量和基于大脑的客观测量（使用功能性近红外光谱技术）。结果表明，观察条件下的先前结果不会自动转移到互动条件下，并且机器人的外观和互动距离是人类在提供建议的情境中对机器人行为感知的重要调节因素。
Recent proposals for how robots should talk to people when they give advice suggest that the same strategies humans employ with other humans are effective for robots as well. However, the evidence is exclusively based on people’s observation of robot giving advice to other humans. Hence, it is not clear whether the results still apply when people actually participate in real interactions with robots. We address this shortcoming in a novel systematic mixed-methods study where we employ both survey-based subjective and brain-based objective measures (using functional near infrared spectroscopy). The results show that previous results from observation conditions do not transfer automatically to interaction conditions, and that robot appearance and interaction distance are important modulators of human perceptions of robot behavior in advice-giving contexts.