Autonomous Navigation of Mobile Robot based on Sensor

Autonomous Navigation of Mobile Robot based on Sensor

ID:39755801

大小:1.76 MB

页数:6页

时间:2019-07-10

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1、The2010IEEE/RSJInternationalConferenceonIntelligentRobotsandSystemsOctober18-22,2010,Taipei,TaiwanAutonomousNavigationofMobileRobotbasedonDGPS/INSSensorFusionbyEKFinSemi-outdoorStructuredEnvironmentHeesungChae,Christiand,SunglokChoi,WonpilYu,JaeilChoElectronicsandTelecommunicationResearchIns

2、titute엉navigation,andthevariousmilitaryarmaments.AlthoughitAbstract—AlthoughGPS/DGPSbecomethedominantlocalizationsolutionintheoutdoorenvironment,itneedshasmanyadvantages,GPSsignalsarealwaysnotavailableassistantsensorsoralgorithmsforthecoveringtheareanottobecausethefeeblesignalsofGPScanbedist

3、urbedbyhighgetthepositioninformationfromGPS.Especially,inthebuildings,roadsidetreesindowntownoramongothers.robotnavigation,thesensorfusionalgorithmisneeded.InTheotherrobotlocalizationresearchistousetherelativeaddition,itishardtogetthepositioninformationattheareasensors(oritcanbedescribedsuch

4、asdeadreckoningsurroundedthehighbuildingssuchasthedowntownbecausesensors-DR)contrarytotheGPSwhichprovidethepositionGPSsignalsissofeeble.Therefore,thispaperillustratesaninformationbymeansofanabsolutemeasurement[2].Theefficientmethodfortheoutdoorlocalizationincorporatingrelativesensors,e.g.,ro

5、botodometerandinertialDGPS,Encoder,andIMUsensorbasedonEKF.Toshowthemeasurementunit(IMU),providethelocationandposelocalizationperformancesoftheproposedfusionalgorithm,informationrelativetotheinitialstate.Incontrast,thewehaveimplementedtheproposedalgorithmandappliedtheabsolutesensorslikeGPScan

6、providetheabsolutepositioninadvertisingrobotplatformwhichisoperatingwellduring80certaincoordinatesystems.Boththeabsolutesensorsandthedaysintherealsemi-outdoorstructuredenvironment.Therelativesensors,havedifferentadvantagesanddisadvantagesproposedsensorfusionalgorithmandtheexperimentalasstate

7、dabove,sofromthatreasons,manyresearchershaveresultsshowedthefeasibilityofournovelsensorfusionbeendevelopedalotoffusionalgorithms.Forthesensoralgorithm.fusion,classicalapproachestothestateestimateproblemforanonlinearstochasticsystemincludetheextende

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