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An Improved Recurrent Network for Online Equality-Constrained Quadratic Programming Read chapter Read first chapter

2016 | OriginalPaper | Chapter

Towards Robot Self-consciousness (I): Brain-Inspired Robot Mirror Neuron System Model and Its Application in Mirror Self-recognition

Authors : Yi Zeng, Yuxuan Zhao, Jun Bai

Published in: Advances in Brain Inspired Cognitive Systems

Publisher: Springer International Publishing

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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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Footnotes
1
Robot Self-Consciousness Project: http://​bii.​ia.​ac.​cn/​robot-self.
 
2
Robot Self-Consciousness Project: http://​bii.​ia.​ac.​cn/​robot-self.
 
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Metadata
Title
Towards Robot Self-consciousness (I): Brain-Inspired Robot Mirror Neuron System Model and Its Application in Mirror Self-recognition
Authors
Yi Zeng
Yuxuan Zhao
Jun Bai
Copyright Year
2016
Book
Advances in Brain Inspired Cognitive Systems

Print ISBN: 978-3-319-49684-9

Electronic ISBN: 978-3-319-49685-6

Copyright Year: 2016

DOI
https://doi.org/10.1007/978-3-319-49685-6_2

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