The iCub Platform: A Tool for Studying Intrinsically Motivated Learning

  • Lorenzo Natale
  • Francesco Nori
  • Giorgio Metta
  • Matteo Fumagalli
  • Serena Ivaldi
  • Ugo Pattacini
  • Marco Randazzo
  • Alexander Schmitz
  • Giulio Sandini


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.


Force Control Motivate Learning Software Architecture Tactile Sensor Real Robot 
These keywords were added by machine and not by the authors. This process is experimental and the keywords may be updated as the learning algorithm improves.



The research leading to these results has received funding from the European Union Seventh Framework Programme FP7/2007-2013 under grant agreements No 231500 (ROBOSKIN), No 214668 (ITALK), and No 215805 (CHRIS).


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Copyright information

© Springer-Verlag Berlin Heidelberg 2013

Authors and Affiliations

  • Lorenzo Natale
    • 1
  • Francesco Nori
    • 1
  • Giorgio Metta
    • 1
  • Matteo Fumagalli
    • 1
  • Serena Ivaldi
    • 1
  • Ugo Pattacini
    • 1
  • Marco Randazzo
    • 1
  • Alexander Schmitz
    • 1
  • Giulio Sandini
    • 1
  1. 1.Department of Robotics, Brain and Cognitive SciencesIstituto Italiano di TecnologiaGenovaItaly

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