Adapting Robot Behavior based on Interaction

Projektinformationen

ARBI

ID Finanzhilfevereinbarung: 220368

Projekt abgeschlossen

Startdatum 1 August 2008

Enddatum 31 Juli 2010

Finanziert unter

• Specific programme "People" implementing the Seventh Framework Programme of the European Community for research, technological development and demonstration activities (2007 to 2013)

Gesamtkosten € 161 942,68

EU-Beitrag € 161 942,68

Koordiniert durch

CENTRE NATIONAL DE LA RECHERCHE SCIENTIFIQUE CNRS
France

Ziel

Having robots that are able to understand, communicate and coordinate with humans executing daily tasks is one of the dreams of society. Moreover, when people interact with robots, they expect the robots to behave in a certain manner, and tend to apply them social models, similarly as how they behave when meeting a new person. Therefore, besides typical perception, reasoning and motion abilities (which have been largely studied so far), the robots also need to have certain abilities to enhance their social behavior when interacting with people. Such abilities are: (i) being proactive, i.e. capability to propose tasks when detecting relevant context, instead of waiting for the human to explicitly ask for something, (ii) perform understandable actions, i.e. show intentions so the human can easily understand and be aware of the robot's actions, (iii) achieve social acceptance, i.e. take into account human preferences so the human feels comfortable with the robot's task execution, (iv) learn, i.e. not only to improve the current knowledge of the robot, but to increase it and to adapt its behavior to the different contexts it may encounter. The main goal of this project is to provide the robot with a reasoning approach to select the most appropriate task execution based on the humans’ preferences and social facts and to improve the robot's behavior as the experience with humans increases. To this end, we propose to design a decisional framework that includes a user modeling approach (stereotype based) and a machine learning technique (case-based reasoning). To evaluate the approach, experiments in simulation and using real robots will be performed.

Wissenschaftliches Gebiet

• natural sciences › computer and information sciences › artificial intelligence › machine learning

Schlüsselbegriffe

• Computer engineering
• artificial intelligence

Programm/Programme

• FP7-PEOPLE - Specific programme "People" implementing the Seventh Framework Programme of the European Community for research, technological development and demonstration activities (2007 to 2013)

Thema/Themen

• PEOPLE-2007-2-1.IEF - Marie Curie Action: "Intra-European Fellowships for Career Development"

Aufforderung zur Vorschlagseinreichung

FP7-PEOPLE-2007-2-1-IEF
Andere Projekte für diesen Aufruf anzeigen

Finanzierungsplan

MC-IEF - Intra-European Fellowships (IEF)

Koordinator

CENTRE NATIONAL DE LA RECHERCHE SCIENTIFIQUE CNRS

Kontakt Verwaltung

Armelle Barelli (Ms.)

• EU-Beitrag: € 161 942,68
• Adresse: RUE MICHEL ANGE 3 ; 75794 Paris ; Frankreich
• Region: Ile-de-France › Ile-de-France › Paris
• Aktivitätstyp: Research Organisations
• Gesamtkosten: Keine Daten