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 of 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 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.
|Title of host publication||Intrinsically Motivated Learning in Natural and Artificial Systems|
|Publisher||Springer-Verlag Berlin Heidelberg|
|Number of pages||26|
|ISBN (Print)||364232374X, 9783642323744|
|Publication status||Published - 2013 Nov 1|
ASJC Scopus subject areas
- Computer Science(all)