Learning at the Ends: From Hand to Tool Affordances in Humanoid Robots

9 Apr 2018Giovanni SaponaroPedro VicenteAtabak DehbanLorenzo JamoneAlexandre BernardinoJosé Santos-Victor

One of the open challenges in designing robots that operate successfully in the unpredictable human environment is how to make them able to predict what actions they can perform on objects, and what their effects will be, i.e., the ability to perceive object affordances. Since modeling all the possible world interactions is unfeasible, learning from experience is required, posing the challenge of collecting a large amount of experiences (i.e., training data)... (read more)

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