Robot in the Mirror: Toward an Embodied Computational Model of Mirror Self-Recognition

Kód výsledku v 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>

Výsledek na webu

<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>

Jazyk výsledku

angličtina

Název v původním jazyce

Robot in the Mirror: Toward an Embodied Computational Model of Mirror Self-Recognition

Popis výsledku v původním jazyce

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.

Název v anglickém jazyce

Robot in the Mirror: Toward an Embodied Computational Model of Mirror Self-Recognition

Popis výsledku anglicky

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.

Druh

J_SC - Článek v periodiku v databázi SCOPUS

CEP obor

—

OECD FORD obor

50103 - Cognitive sciences

Projekt

<a href="/cs/project/GJ17-15697Y" target="_blank" >GJ17-15697Y: Automatická kalibrace robotů a bezpečná fyzická interakce s člověkem inspirovaná reprezentacemi těla v mozku primátů</a><br>

Návaznosti

P - Projekt vyzkumu a vyvoje financovany z verejnych zdroju (s odkazem do CEP)

Rok uplatnění

2021

Kód důvěrnosti údajů

S - Úplné a pravdivé údaje o projektu nepodléhají ochraně podle zvláštních právních předpisů

Název periodika

KI - Künstliche Intelligenz, German Journal on Artificial Intelligence

ISSN

0933-1875

e-ISSN

0933-1875

Svazek periodika

35

Číslo periodika v rámci svazku

1

Stát vydavatele periodika

DE - Spolková republika Německo

Počet stran výsledku

15

Strana od-do

37-51

Kód UT WoS článku

000609092100001

EID výsledku v databázi Scopus

2-s2.0-85099667995