An Intelligent Color Image Recognition and Mobile Control System for Robotic Arm

A. Yao, H. C. Chen
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引用次数: 1

Abstract

The aim of this study is to develop intelligent color recognition, mobile control, and monitoring system for a pick-and-place robotic arm for manufacturing systems. The demand for smart manufacturing factories with real-time control of fabricating processes and traceability of production information is increasing urgently. Generally speaking, a smart manufacturing facility is usually composed of sensing, computing, control, and communication technologies together. In this study, the three-tier architecture of the Internet of things (IoT) was adopted as a guideline to design mobile devices to control and monitor a color image recognition and alarm monitoring system by using Raspberry Pi and a web page database. The practical results and contributions of this study are as follows:  With integrating the techniques of advanced BR PLC, mobile devices and APP, color image recognition, Raspberry Pi microcomputer, and MySQL database technologies together, (1) the mobile control and monitoring system is able to supervise a real-time manufacturing plant anywhere and anytime with mobile devices easily; (2) the color identification system can identify and classify different color work-piece precisely, and the identification results are recorded for remote database platform; (3) the collected data are analyzed and displayed on mobile devices through the web database for field operators and engineers promptly.  It provides a very successful practical paradigm to promote conventional factories to meet industry 4.0.
机械臂智能彩色图像识别与移动控制系统
本研究的目的是为制造系统的拾取机械臂开发智能颜色识别、移动控制和监测系统。对具有制造过程实时控制和生产信息可追溯性的智能制造工厂的需求日益迫切。一般来说,智能制造设施通常由传感、计算、控制和通信技术共同组成。本研究以物联网(IoT)的三层架构为指导,设计移动设备,利用树莓派和网页数据库对彩色图像识别报警监控系统进行控制和监控。本研究的实际成果和贡献如下:将先进的BR PLC技术、移动设备和APP技术、彩色图像识别技术、树莓派微机技术、MySQL数据库技术集成在一起,实现了移动控制与监控系统可以方便地随时随地通过移动设备对制造工厂进行实时监控;(2)颜色识别系统可以对不同颜色的工件进行精确的识别和分类,并将识别结果记录到远程数据库平台;(3)通过web数据库对采集到的数据进行分析,并在移动设备上及时显示,供现场操作人员和工程师使用。它为推动传统工厂适应工业4.0提供了一个非常成功的实践范例。
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CiteScore
3.10
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