Multi-objects detection and classification using Vision Builder for autonomous assembly

Pattaraporn Taptimtong, C. Mitsantisuk, Kanyakorn Sripattanaon, Chayanit Duangkaew, Nichakul Pewleungsawat
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引用次数: 3

Abstract

in this paper, we proposed the methods of object detection and object classification to obtain the location information of each objects on the placement mat through the state diagram process using Vision Builder for Automated inspection (AI). By using the state diagram design detect and classify object on placement mat found that the state diagram can detect and classify almost it objects, both objects with similar surface pattern and objects with similar size. The location of the objects data can be detected and classified have the accuracy is about ±0.5 millimeter. And after using this object’s location data with the automation system, it was found that the robot moved to the position of the object correctly and was able to pick the object for assembly.
基于Vision Builder的自主装配多目标检测与分类
在本文中,我们提出了物体检测和物体分类的方法,利用Vision Builder for Automated inspection (AI)通过状态图处理获得放置垫上每个物体的位置信息。通过使用状态图设计对放置垫上的物体进行检测和分类,发现状态图几乎可以对表面图案相似的物体和尺寸相似的物体进行检测和分类。对物体的位置数据进行检测和分类,精度约为±0.5毫米。将该物体的位置数据与自动化系统结合使用后,发现机器人能够正确地移动到物体的位置,并能够选择物体进行组装。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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