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Integrierte Multi-Sensor-Fusion für die simultane Lokalisierung und Kartenerstellung für mobile Robotersysteme

dc.contributor.authorEmter, Thomas
dc.date.accessioned2025-03-08T06:51:46Z
dc.date.available2025-03-08T06:51:46Z
dc.date.issued2021
dc.date.submitted2021-07-23T15:11:28Z
dc.identifierONIX_20210723_9783731510741_12
dc.identifier1863-6489
dc.identifierhttps://library.oapen.org/handle/20.500.12657/50173
dc.identifier.urihttps://doab-dev.siscern.org/handle/20.500.12854/185633
dc.description.abstractIn this work, probabilistic methods for combining multiple sensors utilizing multi-sensor fusion for robust and precise localization and mapping in heterogeneous outdoor environments are presented. Aspects of increasing the reliability of landmark recognition are highlighted, as well as the integration of additional absolute and relative sensors using advanced filtering techniques.
dc.languageGerman
dc.relation.ispartofseriesKarlsruher Schriften zur Anthropomatik
dc.rightsopen access
dc.subject.otherMobile Robotersysteme
dc.subject.otherMulti-Sensor-Fusion
dc.subject.otherLokalisierung
dc.subject.otherKartierung
dc.subject.otherSLAM
dc.subject.otherMobile robotic systems
dc.subject.othermulti-sensor fusion
dc.subject.otherlocalization
dc.subject.othermapping
dc.subject.otherthema EDItEUR::U Computing and Information Technology::UY Computer science::UYA Mathematical theory of computation::UYAM Maths for computer scientists
dc.titleIntegrierte Multi-Sensor-Fusion für die simultane Lokalisierung und Kartenerstellung für mobile Robotersysteme
dc.typebook
oapen.identifier.doi10.5445/KSP/1000128137
oapen.relation.isPublishedBy68fffc18-8f7b-44fa-ac7e-0b7d7d979bd2
oapen.relation.isbn9783731510741
oapen.imprintKIT Scientific Publishing
oapen.pages272
oapen.place.publicationKarlsruhe
dc.seriesnumber46
dc.abstractotherlanguageIn this work, probabilistic methods for combining multiple sensors utilizing multi-sensor fusion for robust and precise localization and mapping in heterogeneous outdoor environments are presented. Aspects of increasing the reliability of landmark recognition are highlighted, as well as the integration of additional absolute and relative sensors using advanced filtering techniques.
dc.anonymityAll identities known
dc.peerreviewid51a542ec-eaeb-47c2-861d-6022e981a97a
dc.peerreviewtitleDissertations in Series (Dissertationen in Schriftenreihe)
dc.openreviewNo
dc.responsibilityBooks or series editor
dc.stagePre-publication
dc.reviewtypeFull text
dc.reviewertypeEditorial board member
dc.reviewertypeExternal peer reviewer


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