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This paper proposes a hierarchical model to model the multi-modal information in grasping based on deep belief network. In the network, one modal information is self-organized to extract statistical information of given data, and different modal information are easily integrated in the hierarchical architecture. For the learning data, the joint angles, tactile sensors, images of hand and object to be grasped are given based on the dynamics simulator. After learning, the proposed network can recall the sensor information when grasping from the object image.

2A1-F22 Acquiring multimodal representation of hand grasping based on Deep Belief Nets