From force control and sensory-motor informations to mass discrimination

  • Authors:
  • Sébastien Razakarivony;Philippe Gaussier;Fathi Ben Ouezdou

  • Affiliations:
  • ETIS, UMR, CNRS, Université de Cergy Pontoise, ENSEA, Cergy, France;ETIS, UMR, CNRS, Université de Cergy Pontoise, ENSEA, Cergy, France;LISV-EA, Université de Versailles Saint Quentin, Vélizy, France

  • Venue:
  • SAB'10 Proceedings of the 11th international conference on Simulation of adaptive behavior: from animals to animats
  • Year:
  • 2010

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Abstract

Human adults know that usually, big objects are heavier than small ones if these objects are quite similar, in the same material for example. They have a general idea of the weight affordances about the every-day life objects. This paper presents a neural network architecture coupled with a simple linear actuator using force control, designed to use sensory-motor and visual informations during manipulation to learn how to recognize objects of different masses. After learning the association of sensory-motor informations through time with a particular object, our architecture can discriminate different masses and give relevant information for unknown objects, consequently, the objects are associated to some of their inferred physical properties.