外文翻译多模态六自由度力视觉传感器融合的姿态跟踪Word格式文档下载.docx

外文翻译多模态六自由度力视觉传感器融合的姿态跟踪Word格式文档下载.docx

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外文翻译多模态六自由度力视觉传感器融合的姿态跟踪@#@附录A@#@Multi-modalForce/VisionSensorFusionin6-DOFPoseTracking@#@Abstract—Sensorbasedrobotcontrolallowsmanipulationindynamicanduncertainenvironments.Visioncanbeusedtoestimate6-DOFposeofanobjectbymodel-basedposeestimationmethods,buttheestimateisnotaccurateinalldegreesoffreedom.Forceoffersacomplementarysensormodalityallowingaccuratemeasurementsoflocalobjectshapewhenthetooltipisincontactwiththeobject.Asforceandvisionarefundamentallydifferentsensormodalities,theycannotbefuseddirectly.Wepresentamethodwhichfusesforceandvisualmeasurementsusingpositionalinformationoftheend-effector.Bytransformingthepositionofthetooltipandthecameratoasamecoordinateframeandmodelingtheuncertaintiesofthevisualmeasurement,thesensorscanbefusedtogetherinanExtendedKalmanfilter.Experimentalresultsshowgreatlyimprovedposeestimateswhenthesensorfusionisused.@#@I.INTRODUCTION@#@Robotcontrolinunstructuredenvironmentsisachallengingproblem.Simplepositionbasedcontrolisnotadequate,ifthepositionoftheworkpieceisunknownduringmanipulationasuncertaintiespresentinrobottaskpreventtherobotfromfollowingapreprogrammedtrajectory.Sensorbasedmanipulationallowsarobottoadapttoadynamicanduncertainenvironment.Withsensorstheuncertaintiesoftheenvironmentcanbemodeledandtherobotcantakeactionsbasedonthesensoryinput.Invisualservoingtherobotiscontrolledbasedonthesensoryinputfromavisualsensor.A3-Dmodeloftheworkpiececanbecreatedand6-DOFposeoftheobjectcanbedeterminedbyposeestimationalgorithms.Visualservoingenablessuchtasksastrackingamovingobjectwithanend-effectormountedcamera.However,asinglecameravisualmeasurementisoftennotaccurateinalldegreesoffreedom.Onlytheobjecttranslationsperpendiculartothecameraaxiscanbedeterminedaccurately.Objecttranslationalongthecameraaxisisdifficulttomeasureasevenalargechangeinobjectdistanceinducesonlyasmallchangeinimage.Thesameappliesfortherotationsasonlytherotationaroundthecameraaxiscanbedeterminedaccuratelywhereasrotationsaroundtheoffaxesyieldonlyadiminishingchangeinimage.Visioncanbecomplementedbyothersensormodalitiesinordertoalleviatetheseproblems.Withatactileorforcesensorthelocalshapeoftheobjectcanbeprobed.Whenthetooltipisincontactwithanobjectandthepositionofthetooltipisknown,informationabouttheobjectcanbeextracted.However,asingletooltipmeasurementcanonlygiveonepointontheobjectsurface.Withoutotherinformationthismeasurementwouldbeuselessaswedonotknowonwhichlocationoftheobjectthemeasurementistaken.Alsoiftheobjectismovingthepointofcontactcanmoveevenifthepositionofthetooltipisstationary.Combiningaforcesensorwithvisionwouldseemappealingasthesetwosensorscancomplementeachother.Sincetheforceandvisionmeasureafundamentallydifferentsensormodalitytheinformationfromthesesensorscannotbefuseddirectly.Visioncangivethefullposeofanobjectwithrespecttothecamera,butforcesensorcanmeasureforcesonlylocally.Whentheforcesensorisusedonlytodetectifthetooltipisincontactwiththeobject,nootherinformationcanbegained.Combiningthisbinaryinformationwithvisualmeasurementrequiresthatboththepositionofthetooltipandthecameraareknowninthesamecoordinateframe.Thiscanbeachievedastheincrementalencodersorjointanglesensorsoftherobotcandeterminethepositionoftherobotend-effectorinworldcoordinates.Ifalsothehand-eyecalibrationofthecameraandthetoolgeometriesareknown,bothofthemeasurementscanbetransformedintoworldcoordinateframe.Asingletooltipmeasurementcanonlygiveconstraintstotheposeoftheobjectbutnotthefullpose.Thereforeasinglemeasurementismeaninglessunlessitcanbefusedwithothersensormodalitiesorovertime.Combiningseveralsensormodalitiesormultiplemeasurementsovertimecanreducetheuncertaintyofthemeasurements,butinordertofusethemeasurementstheuncertaintyofeachindividualmeasurementmustbeestimated.Alsothesensordelayofthevisualmeasurementsmustbetakenintoaccountwhenfusingthemeasurements.Especially,eye-inhandconfigurationrequiresaccuratesynchronizationofthepositionalinformationandvisualmeasurement.Otherwisevisionwillgiveerroneousinformationwhiletheend-effectorisinmotion.@#@Inthispaper,wepresenthowvisionandforcecanbefusedtogethertakingintoaccounttheuncertaintyofeachindividualmeasurement.Amodelbasedposeestimationalgorithmisusedtoextracttheunknownposeofamovingtarget.TheuncertaintyoftheposedependsontheuncertaintyofthemeasuredfeaturepointsinimageplaneandthisuncertaintyisprojectedintoCartesianspace.Atooltipmeasurementisusedtoprobethelocalshapeoftheobjectbymovingontheobjectsurfaceandkeepingaconstantcontactforce.AnExtendedKalmanfilter（EKF）isthenusedtofusethemeasurementsovertimebytakingintoaccounttheuncertaintyofeachindividualmeasurement.Toourknowledgethisisthefirstworkusingcontactinformationtocompensatetheuncertaintyofvisualtrackingwhilethetooltipisslidingontheobjectsurface.@#@II.RELATEDWORK@#@ReductionofmeasurementerrorsandfusionofseveralsensorymodalitiesusingaKalmanfilter（KF）frameworkiswidelyusedinrobotics,forexample,in6-DOFposetracking[1].However,invisualservoingcontextKalmanfiltersaretypicallyusedonlyforfilteringuncertainvisualmeasurementsanddonottakeintoaccountthepositionalinformationoftheend-effector.Wilsonetal.[2]proposedtosolvetheposeestimationproblemforposition-basedvisualservoingusingtheKFframeworkasthiswillbalancetheeffectofmeasurementuncertainties.Lippielloetal.proposeamethodforcombiningvisualinformationfromseveralcamerasandtheposeoftheendeffectortogetherinKF[3].However,intheirapproachestheKFcanbeunderstoodasasingleiterationofaniterativeGauss-Newtonprocedureforposeestimation,andassuchisnotlikelytogiveoptimalresultsforthenon-linearposeestimationproblem.@#@Controlandobservationaredualproblems.Combiningofforceandvisionisoftendoneonthelevelofcontrol[4],[5],[6].Asthereisnocommonrepresentationforthetwosensormodalitiescombiningtheinformationinoneobservationmodelisnotstraightforward.Previousworkoncombininghapticinformationwithvisioninobservationlevelprimarilyusesthetwosensorsseparately.Visionisusedtogeneratea3Dmodelofanobjectandaforcesensortoextractphysicalpropertiessuchasstiffnessoftheobject[7].Pomaresetal.combinedaforcesensorandaneye-in-handcamerausingstructuredlighttodetectchangesinthecontactsurface[8].Visionisfirstusedtodetectzoneslikelytohavediscontinuitiesonthesurfaceandtheforcesensorisusedforverifyingthediscontinuity.@#@Ourworkcombinescontactinformationwithvisiontoextractmoreaccurateinformationoftheobjectpose.Weassumeaconstantstiffnessfortheobjectmakingitpossibletousethetooltipmeasurementsfordeterminingtheobjectpositionandorientation.Themethodisindependentofthefrictionandcanbeusedevenwhenthetooltipisslidingontheobjectsurfacewhiletheobjectisinmotion.@#@In[9]arobotwasusedtoprobetheposeofanobjectaswellascontactparameters.However,theproposedapproachusedvisiononlytoestimatetheposeofthetoolandnottheposeoftheobject.Ourapproachusesvisiontoestimatetheposeoftheobject,andthepositionofthetooltipaswellastheposeofthecameraareobtainedfromthejointsensorsofaparallelmanipulator.Analgorithmpresentedin[10]combinesvisionwithforceandjointanglesensors.Acamerafixedtotheworldframeaswellaswristforcesensorandjointsensorsofan6-DOFindustrialrobotarefusedinanEKF.Whiletheirapproachtakesadvantageoftheforcesensormeasurementsdirectlyintheposeestimateaswellasthepositionalinformationfromthejointsensors,theyassumefrictionlesspointcontactmakingitimpossibletousethesensorfusionwhilethetooltipismovingonaphysicalsurface.@#@III.MODELBASEDPOSEESTIMATION@#@Theposeofanobjectrelativetoacameraisobtainablewithmodelbasedposeestimationmethods.Weusedmarkerbasedtrackingwithapredefined3-Dmarkermodel.Themarkersystemwasdesignedsothatperspectiveprojectiondoesnotcauseinaccuraciesindeterminingthemarkerlocation.Inourapproachthemarkerfeaturesarepointsanddonotsufferfromperspectiveprojection.Eachmarkerconsistofthreecornerswhichcanberecognizedwithcornerextractionmethods[11].ThemarkersystemandcoordinateaxesoftheestimatedrelativeposeareshowninFig.1.@#@Withmodelbasedpose-estimationtheposeoftheobjectrelativetothecameraCTOcanbedeterminediftheintrinsiccameraparametersareknown.Poseestimationmethodsrequireatleastthree2-D–3-Dfeaturepairsthatarenotonthesameline.AninitialguessfortheposewascalculatedusingDeMenthon’smodel-basedposeestimationmethod[12].However,thisapproachdoesnotconvergetoalocaloptimumoftheposeandthereforealocalgradientdescentapproachwasusedtofinetunethepose.@#@Inoursetupthecameraisattachedrigidlytotheendeffector,butitisnotinthecenteroftheend-effector.TransformationfromthecameratotheobjectCTOismea-suredwithvision.Thetranslationandrotationofthecamerarespecttotheendeffec-torEETCmustbe