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1、IEEETRANSACTIONSONROBOTICSANDAUTOMATION,VOL.17,NO.3,JUNE2001229ASolutiontotheSimultaneousLocalizationandMapBuilding(SLAM)ProblemM.W.M.GaminiDissanayake,Member,IEEE,PaulNewman,Member,IEEE,StevenClark,HughF.Durrant-Whyte,Member,IEEE,andM.CsorbaAbstract—Thesimultaneouslocal
2、izationandmapbuildingrangeofapplicationswhereabsolutepositionorprecisemap(SLAM)problemasksifitispossibleforanautonomousvehicleinformationisunobtainable,including,amongstothers,au-tostartinanunknownlocationinanunknownenvironmentandtonomousplanetaryexploration,subseaautono
3、mousvehicles,thentoincrementallybuildamapofthisenvironmentwhilesi-autonomousair-bornevehicles,andautonomousall-terrainmultaneouslyusingthismaptocomputeabsolutevehiclelocation.Startingfromtheestimation-theoreticfoundationsofthisproblemvehiclesintaskssuchasminingandconstru
4、ction.developedin[1]–[3],thispaperprovesthatasolutiontotheThegeneralSLAMproblemhasbeenthesubjectofsub-SLAMproblemisindeedpossible.TheunderlyingstructureofthestantialresearchsincetheinceptionofaroboticsresearchSLAMproblemisfirstelucidated.Aproofthattheestimatedmapcommunit
5、yandindeedbeforethisinareassuchasmannedconvergesmonotonicallytoarelativemapwithzerouncertaintyvehiclenavigationsystemsandgeophysicalsurveying.Aisthendeveloped.Itisthenshownthattheabsoluteaccuracyofthemapandthevehiclelocationreachalowerbounddefinednumberofapproacheshavebe
6、enproposedtoaddressboththeonlybytheinitialvehicleuncertainty.Together,theseresultsSLAMproblemandalsomoresimplifiednavigationproblemsshowthatitispossibleforanautonomousvehicletostartinwhereadditionalmaporvehiclelocationinformationismadeanunknownlocationinanunknownenvironm
7、entand,usingavailable.Broadly,theseapproachesadoptoneofthreemainrelativeobservationsonly,incrementallybuildaperfectmapofphilosophies.Themostpopularoftheseistheestimation-the-theworldandtocomputesimultaneouslyaboundedestimateofvehiclelocation.Thispaperalsodescribesasubsta
8、ntialimple-oreticorKalmanfilterbasedapproach.ThepopularityofthismentationoftheSLAMalgorithmonavehicleop
