Object Recognition and Selective Handling by a Robot

被引：0
|
作者：
F. Declercq
R. De Keyser
机构：
[1] University Gent,Department of Control Engineering and Automation
来源：
Journal of Intelligent and Robotic Systems | 1999年 / 25卷
关键词：
invariant object recognition; pattern recognition; neural networks; flexible manufacturing;
D O I：
暂无
中图分类号：
学科分类号：
摘要：
A small flexible production cell has been built around a selectively compliant articulated robot arm. Moving on a conveyor belt, boxes marked with different labels are presented to the robot in a random order. Using a camera and a vision card, the labels on the boxes are recognized. Each one of the labels can be rotated, translated or scaled. Three different invariant feature extraction methods (signature, invariant moments of Hu and Zernike) are compared. A neural net is used to classify the labels. The task of the SCARA robot is to pick up the moving boxes and to sort them according to their labels.
引用
收藏
页码：121 / 132
页数：11
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