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SYSTEM REALIZATION PATH OF VISUAL SORTING ROBOT SYSTEM UNDER BIG DATA ECOLOGICALENVIRONMENT

机译:大数据生态环境下视觉分拣机器人系统的系统实现路径

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Big data ecological environment is the key direction of global science and technology development,which will be conducive to the construction of global science and technology ecosystem.Industrial intelligence has become the development trend of various countries' industries,and the application of machine vision technology to industrial robots has become an important way of industrial intelligence.The main breakthrough point of industrial robot machine vision technology lies in the intelligent classification and positioning of targets.Most of the existing visual industrial robots perform simple workpiece classification based on traditional graphics processing technology.This article introduces the principle and architecture of big data Hadoop technology,designs the motion model and positioning navigation model of the visual sorting robot,proposes the process path to realize the positioning and navigation algorithm of the visual sorting robot,and finally gives the overall implementation and remotely control the operation of the visual sorting robot.At the same time,the hardware design of the visual sorting robot is introduced,the realization path of the image processing of the sorting robot system is discussed,and theoretical research and practical testing are carried out.There are two core problems in the visual robot sorting system,one is image recognition and target tracking based on image processing,and the other is the capture and sorting control strategy based on actual industrial robots.The target to be recognized is goods.This article also expounds the overall scheme of the intelligent sorting process,expounds the functional principle of the system,and verifies the feasibility of the system through specific practices.The experimental results show that the visual sorting system can sort workpieces placed at any position in the working area,with a maximum positioning error of 0.65mm,and the sorting effect is good,meeting the sorting requirements.This study can provide a reliable reference for the construction of global science and technology ecosystem.
机译:大数据生态环境是全球科技发展的关键方向,这将有利于全球科技生态系统的建设。工业智能已成为各国产业的发展趋势,以及机器视觉技术的应用工业机器人已成为工业智能的重要途径。工业机器人机器视觉技术的主要突破点在于目标的智能分类和定位。最现有的视觉工业机器人基于传统图形处理技术进行简单的工件分类。这文章介绍了大数据Hadoop技术的原理和体系结构,设计了视觉分拣机器人的运动模型和定位导航模型,提出了实现了视觉分拣机器人的定位和导航算法的过程路径,最后给出了整体实现并远程控制视觉分拣机器人的操作。同时,介绍了视觉分拣机器人的硬件设计,讨论了分拣机器人系统的图像处理的实现路径,并携带了理论研究和实际测试出来的是视觉机器人排序系统中的两个核心问题,一个是基于图像处理的图像识别和目标跟踪,另一个是基于实际工业机器人的捕获和分拣控制策略。要识别的目标是商品。本文还阐述了智能排序过程的整体方案,阐述了系统的功能原则,并通过具体实践来验证系统的可行性。实验结果表明,实验结果表明,视觉分拣系统可以将工件分类为在任何位置放置的工件工作区域,最大定位误差为0.65mm,分拣效果好,满足排序要求。这项研究可以p Rovide为全球科学和技术生态系统建设的可靠参考。

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