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Abstract robots with an attitude: Applying interpersonal relation models to human-robot interaction

机译:有态度的抽象机器人:将人际关系模型应用于人机交互

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This paper explores new possibilities for social interaction between a human user and a robot with an abstract shape. The social interaction takes place by simulating behaviors such as submissiveness and dominance and analyzing the corresponding human reactions. We used an object that has no resemblance with human features in its shape or expression mode, in order to exclude the effect of these features on the human behavior. An intelligent walk-in closet was made to behave either dominantly or submissively using lighting effects. The behaviors of the closet were rated by participants using the Bem Sex Role Inventory in a pilot study, resulting in the selection of one submissive and one dominant lighting behavior for the closet. Participants' personality was measured using the Social Dominance Orientation questionnaire. These data were then compared to measurements of user satisfaction and feelings of dominance, arousal, and valence after scenario completion. A surprising effect was revealed as participants with a dominant personality reported feeling submissive to a dominant system, while in comparison, persons with a submissive personality felt more dominant in the same condition. Furthermore, it was found that a submissive system was generally more preferred by users. We draw a careful conclusion that people interact differently with systems that show human-like attitudes, than they would in response to similar attitude expressed by other person. These findings need to be investigated further with dominant/submissive nonverbal behaviors that are then simulated on a humanoid robot.
机译:本文探讨了人类用户与具有抽象形状的机器人之间进行社交互动的新可能性。通过模拟诸如顺从和支配等行为并分析相应的人类反应来进行社交互动。为了排除这些特征对人类行为的影响,我们使用了在形状或表达方式上与人类特征不相似的物体。利用照明效果,使智能步入式衣橱表现出显性或非显性的表现。参与者通过一项Bem性角色清单在一项初步研究中对壁橱的行为进行了评估,从而为壁橱选择了一种顺从性和一种主导性照明行为。参与者的人格使用社会主导地位问卷进行了测量。然后将这些数据与用户满意度以及场景完成后的主导,唤醒和效价的度量进行比较。当具有显性人格的参与者报告感觉服从于显性系统时,显示出令人惊讶的效果,而相比之下,具有柔弱人格的人在相同条件下感觉更为显性。此外,发现用户通常更喜欢顺从系统。我们得出一个谨慎的结论,即人们与表现出类似人的态度的系统的交互方式不同,而不是响应他人表达的类似态度。这些发现需要用显性/服从性非言语行为进行进一步研究,然后在类人机器人上进行模拟。

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