ROBOTASK

Action words Learning in a Humanoid Robot by Discovering Tool Affordances via Statistical Inference

 Coordinatore FONDAZIONE ISTITUTO ITALIANO DI TECNOLOGIA 

 Organization address address: VIA MOREGO 30
city: GENOVA
postcode: 16163

contact info
Titolo: Ms.
Nome: Maria Carmela
Cognome: Fierro
Email: send email
Telefono: +39 01071781565
Fax: +39 0107170817

 Nazionalità Coordinatore Italy [IT]
 Totale costo 179˙739 €
 EC contributo 179˙739 €
 Programma FP7-PEOPLE
Specific programme "People" implementing the Seventh Framework Programme of the European Community for research, technological development and demonstration activities (2007 to 2013)
 Code Call FP7-PEOPLE-2013-IEF
 Funding Scheme MC-IEF
 Anno di inizio 2014
 Periodo (anno-mese-giorno) 2014-11-01   -   2016-10-31

 Partecipanti

# participant  country  role  EC contrib. [€] 
1    FONDAZIONE ISTITUTO ITALIANO DI TECNOLOGIA

 Organization address address: VIA MOREGO 30
city: GENOVA
postcode: 16163

contact info
Titolo: Ms.
Nome: Maria Carmela
Cognome: Fierro
Email: send email
Telefono: +39 01071781565
Fax: +39 0107170817

IT (GENOVA) coordinator 179˙739.60

Mappa


 Word cloud

Esplora la "nuvola delle parole (Word Cloud) per avere un'idea di massima del progetto.

robots    statistical    permit    grounding    cognitive    grounded    recently    icub    human    interaction    skills    robotics    theories    language    model    inference    sensorimotor    learning    developmental    robot   

 Obiettivo del progetto (Objective)

Recently, humanoids have started to be employed in linguistic investigations with the dual aim of endowing robots with the capability to communicate and interact with humans, and further understanding the mechanisms underlying language development. The proposed research aims at creating a developmental cognitive model for the iCub humanoid robot for grounding the meaning of language in tool affordances. Despite it is firmly clear that language has to be grounded in sensorimotor experience, recently it has became increasingly evident the importance of going beyond simple sensorimotor grounding. To this end, statistical inference provides an original and innovative methodology that can serve in grounded theories of meaning. Computational modeling, based on statistical inference over hierarchies of flexibly structured representations, can address important problems related to human intelligence and cognition, such as the learning of language and causal relations. This research will permit to endow the iCub robot with the ability to understand language during the interaction with a human tutor and provide an experimental framework for investigating how language interacts with other cognitive processes, such as motor control. Additionally, a human-robot interaction study will permit to analyze how people experience interaction through language with the iCub robot. On the one hand, the proposed artificial cognitive system can progress theories of language learning in robots, with consequent advances in the design of human-robot communication systems, which can lead to a new generation of interactive robots. On the other hand, experiments performed on the model, by generating new predictions, can have important implications in cognitive science. The grant of the fellowship will provide the Researcher with the opportunity to further develop interdisciplinary skills in developmental robotics methods, and transferable skills for R&D in academia and service robotics industry.

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