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An Autonomous Social Robot in Fear

机译:恐惧中的自主社交机器人

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摘要

Currently artificial emotions are being extensively used in robots. Most of these implementations are employed to display affective states. Nevertheless, their use to drive the robot's behavior is not so common. This is the approach followed by the authors in this work. In this research, emotions are not treated in general but individually. Several emotions have been implemented in a real robot, but in this paper, authors focus on the use of the emotion of fear as an adaptive mechanism to avoid dangerous situations. In fact, fear is used as a motivation which guides the behavior during specific circumstances. Appraisal of fear is one of the cornerstones of this work. A novel mechanism learns to identify the harmful circumstances which cause damage to the robot. Hence, these circumstances elicit the fear emotion and are known as fear releasers. In order to prove the advantages of considering fear in our decision making system, the robot's performance with and without fear are compared and the behaviors are analyzed. The robot's behaviors exhibited in relation to fear are natural, i.e., the same kind of behaviors can be observed on animals. Moreover, they have not been preprogrammed, but learned by real inter actions in the real world. All these ideas have been implemented in a real robot living in a laboratory and interacting with several items and people.
机译:当前,人工情感被广泛用于机器人中。这些实现中的大多数都用于显示情感状态。然而,它们不是用来驱动机器人行为的。这是作者在本文中遵循的方法。在这项研究中,情感不是一般性的而是个体性的。在真实的机器人中已经实现了几种情绪,但是在本文中,作者专注于使用恐惧情绪作为避免危险情况的自适应机制。实际上,恐惧是在特定情况下引导行为的动机。对恐惧的评估是这项工作的基石之一。一种新颖的机制可以学会识别导致机器人损坏的有害环境。因此,这些情况引起恐惧情绪,被称为恐惧释放者。为了证明在我们的决策系统中考虑恐惧的优势,比较了有无恐惧的机器人性能,并分析了行为。与恐惧有关的机器人行为是自然的,即可以在动物身上观察到相同的行为。而且,它们尚未经过预编程,而是通过现实世界中的实际交互作用来学习的。所有这些想法已在生活在实验室中并与多个物品和人员交互的真实机器人中实现。

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