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.
This work is within the ANR project Interact ANR-09-CORD-014. The authors would like to thank P. Andry and Y. Delevoye for their help.
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Razakarivony, S., Gaussier, P., Ben Ouezdou, F. (2010). From Force Control and Sensory-Motor Informations to Mass Discrimination. In: Doncieux, S., Girard, B., Guillot, A., Hallam, J., Meyer, JA., Mouret, JB. (eds) From Animals to Animats 11. SAB 2010. Lecture Notes in Computer Science(), vol 6226. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-15193-4_21
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DOI: https://doi.org/10.1007/978-3-642-15193-4_21
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