Robot in the Mirror: Toward an Embodied Computational Model of Mirror Self-Recognition
The result's identifiers
Result code in IS VaVaI
<a href="https://www.isvavai.cz/riv?ss=detail&h=RIV%2F68407700%3A21230%2F21%3A00350803" target="_blank" >RIV/68407700:21230/21:00350803 - isvavai.cz</a>
Result on the web
<a href="https://doi.org/10.1007/s13218-020-00701-7" target="_blank" >https://doi.org/10.1007/s13218-020-00701-7</a>
DOI - Digital Object Identifier
<a href="http://dx.doi.org/10.1007/s13218-020-00701-7" target="_blank" >10.1007/s13218-020-00701-7</a>
Alternative languages
Result language
angličtina
Original language name
Robot in the Mirror: Toward an Embodied Computational Model of Mirror Self-Recognition
Original language description
Self-recognition or self-awareness is a capacity attributed typically only to humans and few other species. The definitions of these concepts vary and little is known about the mechanisms behind them. However, there is a Turing test-like benchmark: the mirror self-recognition, which consists in covertly putting a mark on the face of the tested subject, placing her in front of a mirror, and observing the reactions. In this work, first, we provide a mechanistic decomposition, or process model, of what components are required to pass this test. Based on these, we provide suggestions for empirical research. In particular, in our view, the way the infants or animals reach for the mark should be studied in detail. Second, we develop a model to enable the humanoid robot Nao to pass the test. The core of our technical contribution is learning the appearance representation and visual novelty detection by means of learning the generative model of the face with deep auto-encoders and exploiting the prediction error. The mark is identified as a salient region on the face and reaching action is triggered, relying on a previously learned mapping to arm joint angles. The architecture is tested on two robots with completely different face.
Czech name
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Czech description
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Classification
Type
J<sub>SC</sub> - Article in a specialist periodical, which is included in the SCOPUS database
CEP classification
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OECD FORD branch
50103 - Cognitive sciences
Result continuities
Project
<a href="/en/project/GJ17-15697Y" target="_blank" >GJ17-15697Y: Robot self-calibration and safe physical human-robot interaction inspired by body representations in primate brains</a><br>
Continuities
P - Projekt vyzkumu a vyvoje financovany z verejnych zdroju (s odkazem do CEP)
Others
Publication year
2021
Confidentiality
S - Úplné a pravdivé údaje o projektu nepodléhají ochraně podle zvláštních právních předpisů
Data specific for result type
Name of the periodical
KI - Künstliche Intelligenz, German Journal on Artificial Intelligence
ISSN
0933-1875
e-ISSN
0933-1875
Volume of the periodical
35
Issue of the periodical within the volume
1
Country of publishing house
DE - GERMANY
Number of pages
15
Pages from-to
37-51
UT code for WoS article
000609092100001
EID of the result in the Scopus database
2-s2.0-85099667995