基于FastSLAM的绳系机器人同时定位与地图构建算法-豆柴文库

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基于FastSLAM的绳系机器人同时定位与地图构建算法
Title:SimultaneousLocalizationandMapBuildingforRopeManipulationRobotsusingFastSLAMAlgorithm
Abstract:
Ropemanipulationrobotsplayacrucialroleinvariousfieldssuchasrescueoperations,industrialtasks,andspaceexploration.Accuratesimultaneouslocalizationandmapbuilding(SLAM)isacriticalrequirementfortheserobotstoperformtheirtaskseffectively.Inthispaper,weproposeaFastSLAM-basedalgorithmthatintegratesSLAMwiththeropemanipulationcapabilitiesoftherobot.Thealgorithmisdesignedtoenabletherobottolocalizeitselfinreal-timewhileconstructinganaccuratemapofitsenvironment.Theproposedalgorithmhasbeenevaluatedthroughsimulationsandexperiments,demonstratingitseffectivenessandrobustnessinprovidingaccurateandreliablelocalizationandmapbuildingforropemanipulationrobots.
1.Introduction:
Ropemanipulationrobotsareincreasinglybeingemployedintasksthatinvolvenavigationandmanipulationincomplexanddynamicenvironments.Toperformthesetasksefficiently,accuratelocalizationandmappingareessential.Thesimultaneouslocalizationandmapbuilding(SLAM)problemaddressesthisrequirementbyenablingarobottoestimateitspositionandconstructamapoftheenvironmentsimultaneously.Inthispaper,weproposeaFastSLAM-basedalgorithmspecificallytailoredforropemanipulationrobots,whichaddressesthechallengesassociatedwithaccurateSLAMintheiruniqueoperationalcontext.
2.RelatedWork:
SeveralSLAMalgorithmshavebeenproposedovertheyears,suchasExtendedKalmanFilter(EKF)SLAM,GraphSLAM,andParticleFilterSLAM.However,theseclassicalgorithmshavelimitationswhenitcomestohandlingthecomplexitiesassociatedwithropemanipulationrobots.TheFastSLAMalgorithm,whichcombinesparticlefilterswithaRao-BlackwellizedparticlefilterforefficientSLAM,hasshownpromisingresultsinsimilarroboticapplications.Hence,wechooseFastSLAMasthebasisforouralgorithm.
3.FastSLAMAlgorithmforRopeManipulationRobots:
Theproposedalgorithmoperatesinatwo-stepapproach:landmarkinitializationandresampling,andstateestimationandmapping.Thelandmarkinitializationandresamplingstepfocusesonident