Unsupervised Learning of the Spatial Recognition Ability Using the Correlated Information Extracting Neural Network

Abstract

The Correlated Information Extracting Neural Network has been proposed to extract the common information among multiple kinds of inputs. Applying this neural network to a robot with a visual sensor, the distance to an object could be extracted as the correlated information between motional signals and visual signals after learning. In the case of stereo vision which uses two visual sensors, the output representing the distance, did not depend on the size of the object. When the signals of tactile sensor were added to the neural network, the robot could detect from the visual signals or from the motional signals if the robot touched the object.