oru.sePublikationer
Ändra sökning
RefereraExporteraLänk till posten
Permanent länk

Direktlänk
Referera
Referensformat
  • apa
  • ieee
  • modern-language-association-8th-edition
  • vancouver
  • Annat format
Fler format
Språk
  • de-DE
  • en-GB
  • en-US
  • fi-FI
  • nn-NO
  • nn-NB
  • sv-SE
  • Annat språk
Fler språk
Utmatningsformat
  • html
  • text
  • asciidoc
  • rtf
2D map alignment with region decomposition
Center for Applied Intelligent Systems Research, Halmstad University, Halmstad, Sweden.
Örebro universitet, Institutionen för naturvetenskap och teknik. (Mobile Robotics and Olfaction Lab, Centre for Applied Autonomous Sensor Systems (AASS))ORCID-id: 0000-0001-8658-2985
2019 (Engelska)Ingår i: Autonomous Robots, ISSN 0929-5593, E-ISSN 1573-7527, Vol. 43, nr 5, s. 1117-1136Artikel i tidskrift (Refereegranskat) Published
Abstract [en]

In many applications of autonomous mobile robots the following problem is encountered. Two maps of the same environment are available, one a prior map and the other a sensor map built by the robot. To benefit from all available information in both maps, the robot must find the correct alignment between the two maps. There exist many approaches to address this challenge, however, most of the previous methods rely on assumptions such as similar modalities of the maps, same scale, or existence of an initial guess for the alignment. In this work we propose a decomposition-based method for 2D spatial map alignment which does not rely on those assumptions. Our proposed method is validated and compared with other approaches, including generic data association approaches and map alignment algorithms. Real world examples of four different environments with thirty six sensor maps and four layout maps are used for this analysis. The maps, along with an implementation of the method, are made publicly available online.

Ort, förlag, år, upplaga, sidor
Springer, 2019. Vol. 43, nr 5, s. 1117-1136
Nyckelord [en]
Mobile robots, Mapping, Map alignment, Decomposition, 2D, Sensor map, Robot map, Layout map, Emergency map, Region segmentation, Similarity transformation
Nationell ämneskategori
Robotteknik och automation
Forskningsämne
Datavetenskap
Identifikatorer
URN: urn:nbn:se:oru:diva-71107DOI: 10.1007/s10514-018-9785-7ISI: 000467543000002Scopus ID: 2-s2.0-85050797708OAI: oai:DiVA.org:oru-71107DiVA, id: diva2:1275171
Projekt
ILIAD
Forskningsfinansiär
EU, Horisont 2020KK-stiftelsenTillgänglig från: 2019-01-04 Skapad: 2019-01-04 Senast uppdaterad: 2019-06-18Bibliografiskt granskad

Open Access i DiVA

Fulltext saknas i DiVA

Övriga länkar

Förlagets fulltextScopus

Personposter BETA

Magnusson, Martin

Sök vidare i DiVA

Av författaren/redaktören
Magnusson, Martin
Av organisationen
Institutionen för naturvetenskap och teknik
I samma tidskrift
Autonomous Robots
Robotteknik och automation

Sök vidare utanför DiVA

GoogleGoogle Scholar

doi
urn-nbn

Altmetricpoäng

doi
urn-nbn
Totalt: 258 träffar
RefereraExporteraLänk till posten
Permanent länk

Direktlänk
Referera
Referensformat
  • apa
  • ieee
  • modern-language-association-8th-edition
  • vancouver
  • Annat format
Fler format
Språk
  • de-DE
  • en-GB
  • en-US
  • fi-FI
  • nn-NO
  • nn-NB
  • sv-SE
  • Annat språk
Fler språk
Utmatningsformat
  • html
  • text
  • asciidoc
  • rtf