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Towards robot self-consciousness (I): Brain-inspired robot mirror neuron system model and its application in mirror self-recognition

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Abstract

Mirror Self-Recognition is a well accepted test to identify whether an animal is with self-consciousness. Mirror neuron system is believed to be one of the most important biological foundation for Mirror Self-Recognition. Inspired by the biological mirror neuron system of the mammalian brain, we propose a Brain-inspired Robot Mirror Neuron System Model (Robot-MNS-Model) and we apply it to humanoid robots for mirror self-recognition. This model evaluates the similarity between the actual movements of robots and their visual perceptions. The association for self-recognition is supported by STDP learning which connects the correlated visual perception and motor control. The model is evaluated on self-recognition mirror test for 3 humanoid robots. Each robot has to decide which one is itself after a series of random movements facing a mirror. The results show that with the proposed model, multiple robots can pass the self-recognition mirror test at the same time, which is a step forward towards robot self-consciousness.

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APA

Zeng, Y., Zhao, Y., & Bai, J. (2016). Towards robot self-consciousness (I): Brain-inspired robot mirror neuron system model and its application in mirror self-recognition. In Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics) (Vol. 10023 LNAI, pp. 11–21). Springer Verlag. https://doi.org/10.1007/978-3-319-49685-6_2

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