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Autonomous steel casting recognition and positioning on the unmanned automatic production line based on binocular vision
Author(s): Qingquan Xu; Feng Wu; Ruxi Xiang; Jie Zhou; Xiu Yang
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Paper Abstract

Modern industrial production technology is developing rapidly in recent decades. More and more traditional manual productions are becoming automatic when new automatic technologies are introduced among which machine vision plays an indispensable role. Aiming at the unmanned automatic production line of special steel castings in Shanghai MengTeng automatic technology co., LTD , in this paper an algorithm to recognize and position the special steel castings autonomously is proposed based on the binocular vision theory. The technologies including the pyramid hierarchical matching and the deep neural network are described in detain. The identification and positioning of special steel castings is realized. Its procedures are described completed. Some experiments are implemented by using manipulator to grasp the steel castings and running the proposed algorithm. It proves that the proposed algorithm achieves satisfactory results.

Paper Details

Date Published: 12 November 2019
PDF
Proc. SPIE 11197, SPIE Future Sensing Technologies, 111970U (12 November 2019); doi: 10.1117/12.2542688
Show Author Affiliations
Qingquan Xu, Changzhou Institute of Technology (China)
Feng Wu, Changzhou Institute of Technology (China)
Ruxi Xiang, Changzhou Institute of Technology (China)
Jie Zhou, Changzhou Institute of Technology (China)
Xiu Yang, Changzhou Institute of Technology (China)


Published in SPIE Proceedings Vol. 11197:
SPIE Future Sensing Technologies
Masafumi Kimata; Christopher R. Valenta, Editor(s)

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