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2013 | OriginalPaper | Buchkapitel

The iCub Platform: A Tool for Studying Intrinsically Motivated Learning

verfasst von : Lorenzo Natale, Francesco Nori, Giorgio Metta, Matteo Fumagalli, Serena Ivaldi, Ugo Pattacini, Marco Randazzo, Alexander Schmitz, Giulio Sandini

Erschienen in: Intrinsically Motivated Learning in Natural and Artificial Systems

Verlag: Springer Berlin Heidelberg

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Abstract

Intrinsically motivated robots are machines designed to operate for long periods of time, performing tasks for which they have not been programmed. These robots make extensive use of explorative, often unstructured actions in search for opportunities to learn and extract information from the environment. Research in this field faces challenges that need advances not only on the algorithms but also on the experimental platforms. The iCub is a humanoid platform that was designed to support research in cognitive systems. We review in this chapter the chief characteristics of the iCub robot, devoting particular attention to those aspects that make the platform particularly suitable to the study of intrinsically motivated learning. We provide details on the software architecture, the mechanical design, and the sensory system. We report examples of experiments and software modules to show how the robot can be programmed to obtain complex behaviors involving the interaction with the environment. The goal of this chapter is to illustrate the potential impact of the iCub on the scientific community at large and, in particular, on the field of intrinsically motivated learning.

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The RobotCub project was funded by the European Commission, Project IST-004370, under Strategic Objective 2.3.2.4: Cognitive Systems.

The iCub software and hardware are licensed under the GNU General Public License (GPL) and GNU Free Documentation License (FDL), respectively.

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Titel: The iCub Platform: A Tool for Studying Intrinsically Motivated Learning
verfasst von: Lorenzo Natale
Francesco Nori
Giorgio Metta
Matteo Fumagalli
Serena Ivaldi
Ugo Pattacini
Marco Randazzo
Alexander Schmitz
Giulio Sandini
Verlag: Springer Berlin Heidelberg
Buch: Intrinsically Motivated Learning in Natural and Artificial Systems
Print ISBN: 978-3-642-32374-4

Electronic ISBN: 978-3-642-32375-1

Copyright-Jahr: 2013
DOI: https://doi.org/10.1007/978-3-642-32375-1_17

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