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文件名称:针对装配机器人金属高光件特征提取技术研究.pdf
文件大小:3.47 MB
总页数:65 页
更新时间:2025-06-23
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文档摘要

针对装配机器人金属高光件特征提取技术研究

Abstract

Theaccurateacquisitionofgeometricfeaturesandparametersofmechanicalpartsisthe

premiseandkeyoftheassemblyrobottocompletetheassemblytask.Timelyandaccurate

acquisitionofthegeometricfeaturesandparametersofthetargetpartscanimproveproduction

efficiencyandensureproductqualityandproductionsafety.Metalpartsarewidelyusedin

actualproductionandassemblywork,andtheirsurfaceshavespecialreflectivepropertiesto

light.Duetothecomplexfieldenvironmentanddifferentlightconditions,localorevenlarge

areaofhighlightreflectionisoftenproducedwhenindustrialcamerasareusedforimage

acquisitionofmetalparts,whichmakesthefeatureinformationofmetaltargetscoveredbythe

highlight,resultinginthelossoftargetdataandreducingtheoverallqualityoftheimage.In

thispaper,thefollowingresearchiscarriedoutonthesituationthathighlightsappearinthe

imageofmetalpartsinthehighlightenvironmentintheassemblyoperationoftheassembly

robot,whichcoversthegeometricfeaturesofthetargetandleadstolowdetectionrate:

1)Inordertonarrowthesearchscopeoftargetextractionandreducetheinfluenceof

complexbackgroundfactors,theYOLOv5targetdetectionalgorithmisproposedtobeapplied

totheroughlocationofpartstargets.TheexperimentalresultsshowthatthemAPvalueofthe

proposedmodelisupto96.6%forgasketrecognitionand95.9%forgeardetection,which

provestheaccuracyoftheproposedmodelandmeetstheneedsofactualtargetdetection.

2)Aimingattheproblemthathighlightsappearintheimageofmetalpartsduringimage

acquisition,coveringthegeometricfeaturesofthetargetandresultinginlowdetectionrate,a

highlightextractionandrecoveryalgorithmbasedonthecombinationofsaliencydetectionand

fastmovingrepairisproposed.