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Brain-Like Robotics

  • Chapter
Springer Handbook of Bio-/Neuroinformatics

Part of the book series: Springer Handbooks ((SHB))

Abstract

This chapter aims to provide an overview of what is happening in the field of brain like robotics, what the main issues are and how they are being addressed by different authors. It starts by introducing several concepts and theories on the evolution and operation of the brain and provides a basic biological and operational framework as background to contextualize the topic. Building on these foundations, the main body of the chapter is devoted to the different contributions within the robotics community that use brain-like models as a source of inspiration for controlling real robots. These contributions are addressed from two perspectives. On one hand the main cognitive architectures developed under a more or less strict brain-like point of view are presented, offering a brief description of each architecture as well as highlighting some of their main contributions. Then the point of view is changed and a more extensive review is provided of what is being done within three areas that we consider key for the future development of autonomous brain-like robotic creatures that can live and work in human environments interacting with other robots and human beings. These are: Memory, Attention and Emotions. This review is followed by a description of some of the current projects that are being carried out or have recently finished within this field as well as of some robotic platforms that are currently being used. The chapter is heavily referenced in the hope that this extensive compilation of papers and books from the different areas that are relevant within the field are useful for the reader to really appreciate its breadth and beauty.

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Abbreviations

3-D:

three-dimensional

AI:

artificial intelligence

ANN:

artificial neural network

BBD:

brain-based device

BLR:

brain-like robotics

CDR:

cognitive developmental robotics

ERA:

epigenetic robotics architecture

FOA:

focus of attention

IAC:

intelligent adaptive Curiosity

IHDR:

incremental hierarchical discriminant regression

IM:

images line

IMA:

intelligent machine architecture

IOR:

inhibition of return

IT:

infero temporal cortex

LGN:

lateral geniculate nucleus

LTM:

long-term memory

MDB:

multi-level Darwinist brain

MDP:

Markov decision process

MT:

middle temporal cortex

PP:

posterior parietal cortex

SASE:

self-aware and self-effecting architecture

SM:

sensory memory

SOM:

self-organizing map

STM:

short-term memory

VF:

visual field

WTA:

winner-take-all

pSNN:

probabilistic spiking neural network

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Authors and Affiliations

  1. Department of Computer Science, Universidade da Coruña, EPS, Mendizabal s/n, 15403, Ferrol, (A Coruña), Spain

    Richard J. Duro

  2. Escola Politecnica Superior, Department of Computer Science, Universidade da Coruña, 15405, Ferrol, (A Coruña), Spain

    Francisco Bellas

  3. Department of Computer Science, University of A Coruña, Mendizábal s/n, 15403, Ferrol, Spain

    José A. Becerra Permuy

Authors
  1. Richard J. Duro
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  2. Francisco Bellas
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  3. José A. Becerra Permuy
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Corresponding authors

Correspondence to Richard J. Duro , Francisco Bellas or José A. Becerra Permuy .

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Editors and Affiliations

  1. KEDRI – Knowledge Engineering and Discovery Research Institute, Auckland University of Technology, 120 Mayoral Drive, 1010, Auckland, New Zealand

    Nikola Kasabov

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© 2014 Springer-Verlag

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Duro, R.J., Bellas, F., Becerra Permuy, J.A. (2014). Brain-Like Robotics. In: Kasabov, N. (eds) Springer Handbook of Bio-/Neuroinformatics. Springer Handbooks. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-30574-0_57

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  • DOI: https://doi.org/10.1007/978-3-642-30574-0_57

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