Instrinsically motivated robots are machines designed to operate for long periods of time, performing tasks for which they have not been programmed for. These robots make extensive use of explorative, often unstructured actions in search for opportunities to learn and to extract information from the environment. Research in this eld 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 paper the chief characteristics of the iCub robot, devoting particular attention to those aspects that makes 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 paper is to illustrate the potential impact of the iCub on the scientic community at large, but, in particular on the eld of instrinsically motivated learning.
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