Design and simulation robotic arm with computer vision for inspection process

Ghazi Alnowaini, Azmi Alttal, A. Alhaj
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引用次数: 1

Abstract

Different companies compete for control of the size of the commercial markets and to offer quality products. Companies are keen to examine the products and ensure that they are free of any defects or distortions before distributing them in markets in order to preserve the confidence of customers, but manual inspection is expensive and takes a lot of time. Investors tended to use modern technologies to implement the examination process. In this paper, an approach based on the association of robots with a computer vision system is proposed. A robot arm with 4 degrees of freedom is designed by SOLIDWORKS software that takes the cans into the conveyor belt then passes it to the examination room so that an image of the product is taken via camera attached to the computer and the image is processed by the LABVIEW program. The model was simulated using MATLAB, and Arduino microcontroller has been used for controlling the processes perform by the prototype. When a defective product passes a conveyor belt, the system changes the path to remove the product from the production line. The simulation and experimental results proved that the prototype is capable of grasping cans, then detecting the cans finally, taking the defective ones out of the production line. By using this technology in the product sorting process, the productivity will be increased and the quality will be enhanced in a short time. An accuracy of 96% has been accomplished by the proposed system, where of 50 samples only two samples haven’t detected.
基于计算机视觉的机械臂检测过程设计与仿真
不同的公司为了控制商业市场的规模和提供高质量的产品而竞争。为了保持消费者的信心,企业在将产品投放市场之前都热衷于检查产品,确保它们没有任何缺陷或扭曲,但人工检查既昂贵又耗时。投资者倾向于使用现代技术来实施审查过程。本文提出了一种基于机器人与计算机视觉系统关联的方法。利用SOLIDWORKS软件设计了一个4自由度的机械臂,将罐头送入传送带,然后将其传递到检查室,通过连接在计算机上的摄像头拍摄产品图像,并通过LABVIEW程序对图像进行处理。利用MATLAB对模型进行了仿真,并利用Arduino单片机对样机执行的过程进行了控制。当有缺陷的产品通过传送带时,系统改变路径将产品从生产线上移除。仿真和实验结果证明,该原型机能够抓取易拉罐,并对易拉罐进行检测,最终将不合格的易拉罐带出生产线。在产品分选过程中采用该技术,可以在短时间内提高生产效率,提高产品质量。该系统的准确率达到96%,其中50个样本中只有两个样本未检测到。
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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