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Personal identity module using psychoevolutionary emotion theory for social robots

机译:使用心理进化情感理论的社交机器人个人身份模块

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Robots that interacts socially in human being environment should be able to understand and act over it using clues from humans; it includes all types of expression: facial, non-facial, verbal and nonverbal affective expressions. These behaviors need a model capable to compute external and internal information to construct autonomous robots. In this paper, we are proposing a basis for modeling some reflexes inherent to human beings that are responsible by personal identity of each individual. The proposed model is constituted by two reflex modules and an emotion module that are based on psychoevolutionary theory. Then, this model has been inserted in our social architecture as an improvement of old motivational module and evaluated in a simulator. The advantage of the proposed approach from others is the possibility of representing the emotion as an internal function which varies over the time with different types of interaction. The experimental results show that this module is capable to emulate adequately human beings basic reflex in a robot during a simple interaction with a caregiver.
机译:在人类环境中进行社交互动的机器人应该能够利用人类的线索来理解并采取行动;它包括所有类型的表达:面部,非面部,语言和非语言情感表达。这些行为需要一个能够计算外部和内部信息以构建自主机器人的模型。在本文中,我们为模拟人类固有的,由每个人的个人身份负责的反射提供了基础。所提出的模型由基于心理进化论的两个反射模块和一个情感模块组成。然后,此模型作为对旧动机模块的改进而被插入到我们的社会体系结构中,并在模拟器中进行了评估。所提出的方法与其他方法相比的优势在于,可以将情感表示为内部函数,该函数会随着时间的推移而随着交互类型的不同而变化。实验结果表明,该模块能够在与护理人员的简单交互过程中充分模拟人类在机器人中的基本反射。

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