本文選題：自動(dòng)導(dǎo)引小車　切入點(diǎn)：視覺(jué)導(dǎo)引　出處：《中國(guó)計(jì)量大學(xué)》2016年碩士論文　論文類型：學(xué)位論文

【摘要】：制造業(yè)中的物流體系往往采用人工方式進(jìn)行物料搬運(yùn)、裝配,但是隨著勞動(dòng)力成本的上升,這種方式暴露出物流效率低、可靠性低、成本高的問(wèn)題。因此AGV技術(shù)迎來(lái)全新的發(fā)展機(jī)遇,但是傳統(tǒng)的磁導(dǎo)引AGV獲取的偏差信息單一,控制效果差,無(wú)軌導(dǎo)引方式價(jià)格又十分昂貴,本文引入視覺(jué)導(dǎo)引技術(shù),對(duì)制造業(yè)生產(chǎn)線的自動(dòng)化倉(cāng)儲(chǔ)物流問(wèn)題進(jìn)行了研究,主要研究?jī)?nèi)容如下:首先,為解決AGV傳統(tǒng)導(dǎo)引方式獲取偏差信息單一,控制效果差,而無(wú)軌導(dǎo)引方式價(jià)格非常昂貴的問(wèn)題,根據(jù)模塊化的設(shè)計(jì)思想,完成視覺(jué)導(dǎo)引AGV的總體方案設(shè)計(jì),包括AGV機(jī)械結(jié)構(gòu)設(shè)計(jì)、各功能模塊的硬件部分設(shè)計(jì)以及車載控制系統(tǒng)軟件設(shè)計(jì)。其次,闡述了基于機(jī)器視覺(jué)的AGV導(dǎo)引原理,提出采用AGV橫向偏移量e和方向偏差角θ作為導(dǎo)引信息。為實(shí)現(xiàn)對(duì)導(dǎo)引信息的提取,本文基于Visual Studio 2008集成開(kāi)發(fā)環(huán)境配置OpenCV 2.4.4開(kāi)發(fā)包進(jìn)行圖像處理,包括圖像濾波、閾值分割、邊緣檢測(cè)、色帶識(shí)別以及色帶中心線擬合。再次,分析了差速式視覺(jué)導(dǎo)引AGV的軌跡糾偏過(guò)程,并建立AGV軌跡糾偏數(shù)學(xué)模型。根據(jù)建模結(jié)果,糾偏過(guò)程中的兩個(gè)控制變量存在耦合關(guān)系,因此設(shè)計(jì)了二維模糊控制器實(shí)現(xiàn)軌跡糾偏過(guò)程的非線性控制。最后,根據(jù)總體方案設(shè)計(jì),搭建了視覺(jué)導(dǎo)引AGV實(shí)驗(yàn)平臺(tái);通過(guò)實(shí)驗(yàn)驗(yàn)證所設(shè)計(jì)的AGV在圖像處理、負(fù)載能力、糾偏能力、停障能力以及定位精度方面的性能。
[Abstract]:The logistics system in the manufacturing industry often adopts the manual way to carry on the material handling, the assembly, but along with the labor cost rise, this kind of way exposes the logistics efficiency is low, the reliability is low, The problem of high cost. Therefore, AGV technology ushered in a new development opportunity, but the deviation information obtained by traditional magnetic guidance AGV is single, the control effect is poor, and the price of trackless guidance is very expensive. The automatic warehousing logistics problem of manufacturing line is studied. The main contents are as follows: firstly, in order to solve the problem of single deviation information and poor control effect in the traditional AGV guidance mode, the trackless guidance method is very expensive. According to the modular design idea, the overall scheme design of visual guided AGV is completed, including the mechanical structure design of AGV, the hardware design of each functional module and the software design of vehicle control system. Secondly, This paper expounds the principle of AGV guidance based on machine vision, and proposes to use AGV lateral offset e and directional deviation angle 胃 as guidance information. This paper is based on Visual Studio 2008 integrated development environment to configure OpenCV 2.4.4 development kit for image processing, including image filtering, threshold segmentation, edge detection, ribbon recognition and ribbon centerline fitting. The trajectory correction process of differential vision guided AGV is analyzed, and the mathematical model of AGV trajectory correction is established. Therefore, a two-dimensional fuzzy controller is designed to realize the nonlinear control of trajectory correction process. Finally, according to the overall scheme design, a visual guided AGV experimental platform is built, and the designed AGV is verified in image processing and load capacity through experiments. Ability to correct deviation, stop obstacle and position accuracy.
【學(xué)位授予單位】：中國(guó)計(jì)量大學(xué)
【學(xué)位級(jí)別】：碩士
【學(xué)位授予年份】：2016
【分類號(hào)】：TP391.41;TP242

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