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Mood contagion of robot body language in human robot interaction

机译:人机交互中机器人肢体语言的情绪传染

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The aim of our work is to design bodily mood expressions of humanoid robots for interactive settings that can be recognized by users and have (positive) effects on people who interact with the robots. To this end, we develop a parameterized behavior model for humanoid robots to express mood through body language. Different settings of the parameters, which control the spatial extent and motion dynamics of a behavior, result in different behavior appearances expressing different moods. In this study, we applied the behavior model to the gestures of the imitation game performed by the NAO robot to display either a positive or a negative mood. We address the question whether robot mood displayed simultaneously with the execution of functional behaviors in a task can (a) be recognized by participants and (b) produce contagion effects. Mood contagion is an automatic mechanism that induces a congruent mood state by means of the observation of another person's emotional expression. In addition, we varied task difficulty to investigate how the task load mediates the effects. Our results show that participants are able to differentiate between positive and negative robot mood and they are able to recognize the behavioral cues (the parameters) we manipulated. Moreover, self-reported mood matches the mood expressed by the robot in the easy task condition. Additional evidence for mood contagion is provided by the fact that we were able to replicate an expected effect of negative mood on task performance: in the negative mood condition participants performed better on difficult tasks than in the positive mood condition, even though participants' self-reported mood did not match that of the robot.
机译:我们的工作目的是为交互式设置设计类人机器人的身体情绪表达,这种设置可以被用户识别并对与该机器人进行交互的人产生(积极的)影响。为此,我们为类人机器人开发了参数化的行为模型,以通过肢体语言表达情绪。控制行为的空间范围和运动动力学的参数的不同设置会导致表达不同情绪的不同行为外观。在这项研究中,我们将行为模型应用于NAO机器人执行的模仿游戏的手势,以显示积极或消极的情绪。我们解决了这样一个问题:在任务中执行功能行为的同时显示的机器人情绪是否可以(a)被参与者识别和(b)产生传染效应。情绪传染是一种自动机制,可通过观察他人的情绪表达来诱导一致的情绪状态。此外,我们改变了任务难度,以研究任务负载如何介导效果。我们的结果表明,参与者能够区分机器人的积极情绪和消极情绪,并且能够识别我们操纵的行为线索(参数)。此外,自我报告的情绪与机器人在轻松任务条件下表达的情绪相匹配。我们能够复制负面情绪对任务绩效的预期影响,这提供了情绪传染的其他证据:在负面情绪条件下,参与者在困难任务上的表现要比在正面情绪条件下要好,即使参与者的自我报告的心情与机器人的心情不符。

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