Abstract
It is supposed that the human recognizes grasped objects using visual information and somato-sensory information. It should be noticed that the relation between these kinds of sensory information about an object is many-to-many relation and the human must recognize the grasped object from such kinds of information. In our previous work, we have proposed a neural network model that makes an internal representation of an object by integrating visual information and somato-sensory information about the grasped object. In this paper, we confirm that our proposed neural network model can learn the many-to-many relation between these kinds of information using numerical simulation.
