Interpretation of emotional body language displayed by robots

AFFINE '10 Pub Date : 2010-10-29 DOI:10.1145/1877826.1877837
Aryel Beck, Antoine Hiolle, A. Mazel, L. Cañamero
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引用次数: 69

Abstract

In order for robots to be socially accepted and generate empathy they must display emotions. For robots such as Nao, body language is the best medium available, as they do not have the ability to display facial expressions. Displaying emotional body language that can be interpreted whilst interacting with the robot should greatly improve its acceptance. This research investigates the creation of an "Affect Space" [1] for the generation of emotional body language that could be displayed by robots. An Affect Space is generated by "blending" (i.e. interpolating between) different emotional expressions to create new ones. An Affect Space for body language based on the Circumplex Model of emotions [2] has been created. The experiment reported in this paper investigated the perception of specific key poses from the Affect Space. The results suggest that this Affect Space for body expressions can be used to improve the expressiveness of humanoid robots. In addition, early results of a pilot study are described. It revealed that the context helps human subjects improve their recognition rate during a human-robot imitation game, and in turn this recognition leads to better outcome of the interactions.
解读机器人的情感肢体语言
为了让机器人被社会接受并产生同理心,它们必须表现出情感。对于像Nao这样的机器人来说,肢体语言是最好的媒介,因为它们没有表现面部表情的能力。在与机器人互动的同时,表现出可以理解的情感肢体语言,应该会大大提高机器人的接受度。本研究探讨了“情感空间”的创建[1],用于生成机器人可以显示的情感肢体语言。影响空间是通过“混合”(即在不同的情感表达之间插入)来产生新的情感表达。基于情绪的Circumplex模型[2],已经创建了一个肢体语言的情感空间。本文的实验研究了影响空间对特定关键姿势的感知。结果表明,这种身体表情的影响空间可以用来提高仿人机器人的表达能力。此外,还介绍了一项初步研究的初步结果。研究表明,在人机模仿游戏中,情境有助于人类受试者提高识别率,而这种识别反过来又会导致更好的交互结果。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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