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Adaptive Emotional Expression in Robot-Child Interaction

机译:机器人与儿童互动中的自适应情绪表达

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Expressive behaviour is a vital aspect of human interaction. A model for adaptive emotion expression was developed for the Nao robot. The robot has an internal arousal and valence value, which are influenced by the emotional state of its interaction partner and emotional occurrences such as winning a game. It expresses these emotions through its voice, posture, whole body poses, eye colour and gestures. An experiment with 18 children (mean age 9) and two Nao robots was conducted to study the influence of adaptive emotion expression on the interaction behaviour and opinions of children. In a within-subjects design the children played a quiz with both an affective robot using the model for adaptive emotion expression and a non-affective robot without this model. The affective robot reacted to the emotions of the child using the implementation of the model, the emotions of the child were interpreted by a Wizard of Oz. The dependent variables, namely the behaviour and opinions of the children, were measured through video analysis and questionnaires. The results show that children react more expressively and more positively to a robot which adaptively expresses itself than to a robot which does not. The feedback of the children in the questionnaires further suggests that showing emotion through movement is considered a very positive trait for a robot. From their positive reactions we can conclude that children enjoy interacting with a robot which adaptively expresses itself through emotion and gesture more than with a robot which does not do this.
机译:表达行为是人类互动的重要方面。为Nao机器人开发了一种自适应情绪表达模型。机器人具有内部唤醒和效价值,该值受其交互伙伴的情感状态和赢得游戏之类的情感事件的影响。它通过声音,姿势,全身姿势,眼睛颜色和手势来表达这些情感。进行了一项针对18个孩子(平均年龄为9岁)和两个Nao机器人的实验,以研究自适应情绪表达对孩子的互动行为和观点的影响。在受试者内部设计中,孩子们既使用情感模型(使用自适应情绪表达模型)也使用非情感机器人(不使用此模型)进行测验。情感机器人使用该模型的实现对孩子的情绪做出反应,“绿野仙踪”对孩子的情绪进行了解释。通过视频分析和问卷调查来测量因变量,即孩子的行为和意见。结果表明,与对不自适应的机器人相比,儿童对自适应表达的机器人的表现力和积极性更高。孩子们在问卷中的反馈进一步表明,通过运动表现情感被认为是机器人非常积极的特质。从他们的积极反应中,我们可以得出结论,与不这样做的机器人相比,儿童更喜欢与通过情感和手势自适应地表达自己的机器人互动。

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