A self-learning robot vision system

Hisato Kobayashi, Kenko Uchida, Yutaka Matsuzaki

研究成果: Conference contribution

4 被引用数 (Scopus)

抄録

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.

本文言語English
ホスト出版物のタイトル91 IEEE Int Jt Conf Neural Networks IJCNN 91
Place of PublicationPiscataway, NJ, United States
出版社Publ by IEEE
ページ2007-2012
ページ数6
ISBN(印刷版)0780302273
出版ステータスPublished - 1991
外部発表はい
イベント1991 IEEE International Joint Conference on Neural Networks - IJCNN '91 - Singapore, Singapore
継続期間: 1991 11 181991 11 21

Other

Other1991 IEEE International Joint Conference on Neural Networks - IJCNN '91
CitySingapore, Singapore
Period91/11/1891/11/21

ASJC Scopus subject areas

  • Engineering(all)

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