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dc.contributor.authorEmter, Thomas
dc.date.accessioned2021-07-23T15:11:28Z
dc.date.available2021-07-23T15:11:28Z
dc.date.issued2021
dc.identifierONIX_20210723_9783731510741_12
dc.identifier.issn1863-6489
dc.identifier.urihttps://library.oapen.org/handle/20.500.12657/50173
dc.languageGerman
dc.relation.ispartofseriesKarlsruher Schriften zur Anthropomatik
dc.subject.classificationthema EDItEUR::U Computing and Information Technology::UY Computer science::UYA Mathematical theory of computation::UYAM Maths for computer scientistsen_US
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.titleIntegrierte Multi-Sensor-Fusion für die simultane Lokalisierung und Kartenerstellung für mobile Robotersysteme
dc.typebook
oapen.abstract.otherlanguageIn 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.
oapen.identifier.doi10.5445/KSP/1000128137
oapen.relation.isPublishedBy44e29711-8d53-496b-85cc-3d10c9469be9
oapen.relation.isbn9783731510741
oapen.imprintKIT Scientific Publishing
oapen.series.number46
oapen.pages272
oapen.place.publicationKarlsruhe
peerreview.anonymityAll identities known
peerreview.id51a542ec-eaeb-47c2-861d-6022e981a97a
peerreview.open.reviewNo
peerreview.publish.responsibilityBooks or series editor
peerreview.review.stagePre-publication
peerreview.review.typeFull text
peerreview.reviewer.typeEditorial board member
peerreview.reviewer.typeExternal peer reviewer
peerreview.titleDissertations in Series (Dissertationen in Schriftenreihe)


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