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A self-learning robot vision system

Hisato Kobayashi, K. Uchida, Yutaka Matsuzaki

Year
1991
Citations
5

Abstract

The authors propose a self-learning strategy for robot vision systems which are used to identify the position of the target part handled by a robot. They tried to use a neural network as a decision-making system which determines how to move the robot to reach the exact target on the base of the image acquired by the robot eye. The authors taught this function automatically to the neural network. The total system works as follows: (1) a target object is set at a known position, and the position is taught to the system, (2) the robot moves randomly around the target and the neural network learns the relation between the relative positions and images, and (3) after enough learning, the robot can identify the target located at an arbitrary position.< <ETX xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">&gt;</ETX>

Keywords

RobotArtificial intelligenceArtificial neural networkComputer sciencePosition (finance)Set (abstract data type)Computer visionObject (grammar)Robot learningRelation (database)

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