Change search
CiteExportLink to record
Permanent link

Direct link
Cite
Citation style
  • apa
  • harvard1
  • ieee
  • modern-language-association-8th-edition
  • vancouver
  • Other style
More styles
Language
  • de-DE
  • en-GB
  • en-US
  • fi-FI
  • nn-NO
  • nn-NB
  • sv-SE
  • Other locale
More languages
Output format
  • html
  • text
  • asciidoc
  • rtf
Exploiting distinguishable image features in robotic mapping and localization
KTH, School of Computer Science and Communication (CSC), Centres, Centre for Autonomous Systems, CAS.ORCID iD: 0000-0002-1170-7162
KTH, School of Computer Science and Communication (CSC), Computer Vision and Active Perception, CVAP. KTH, School of Computer Science and Communication (CSC), Centres, Centre for Autonomous Systems, CAS. (CAS)ORCID iD: 0000-0002-7796-1438
KTH, School of Computer Science and Communication (CSC), Numerical Analysis and Computer Science, NADA. KTH, School of Computer Science and Communication (CSC), Centres, Centre for Autonomous Systems, CAS.ORCID iD: 0000-0003-2965-2953
KTH, School of Computer Science and Communication (CSC), Numerical Analysis and Computer Science, NADA. KTH, School of Computer Science and Communication (CSC), Centres, Centre for Autonomous Systems, CAS.
2006 (English)In: European Robotics Symposium 2006 / [ed] Christensen, HI, 2006, Vol. 22, 143-157 p.Conference paper, Published paper (Refereed)
Abstract [en]

Simultaneous localization and mapping (SLAM) is an important research area in robotics. Lately, systems that use a single bearing-only sensors have received significant attention and the use of visual sensors have been strongly advocated. In this paper, we present a framework for 3D bearing only SLAM using a single camera. We concentrate on image feature selection in order to achieve precise localization and thus good reconstruction in 3D. In addition, we demonstrate how these features can be managed to provide real-time performance and fast matching, to detect loop-closing situations. The proposed vision system has been combined with an extended Kalman Filter (EKF) based SLAM method. A number of experiments have been performed in indoor environments which demonstrate the validity and effectiveness of the approach. We also show how the SLAM generated map can be used for robot localization. The use of vision features which are distinguishable allows a straightforward solution to the "kidnapped-robot" scenario.

Place, publisher, year, edition, pages
2006. Vol. 22, 143-157 p.
Series
Springer Tracts in Advanced Robotics, ISSN 1610-7438 ; 22
National Category
Computer Science
Identifiers
URN: urn:nbn:se:kth:diva-38301ISI: 000237516900012Scopus ID: 2-s2.0-33845404234ISBN: 3-540-32688-X (print)OAI: oai:DiVA.org:kth-38301DiVA: diva2:436657
Conference
1st European Robotics Symposium (EUROS-06) Location: Palermo, ITALY Date: MAR 16-18, 2006
Available from: 2011-08-24 Created: 2011-08-24 Last updated: 2012-01-17Bibliographically approved

Open Access in DiVA

No full text

Scopus

Authority records BETA

Jensfelt, PatricFolkesson, JohnKragic, Danica

Search in DiVA

By author/editor
Jensfelt, PatricFolkesson, JohnKragic, DanicaChristensen, Henrik I.
By organisation
Centre for Autonomous Systems, CASComputer Vision and Active Perception, CVAPNumerical Analysis and Computer Science, NADA
Computer Science

Search outside of DiVA

GoogleGoogle Scholar

isbn
urn-nbn

Altmetric score

isbn
urn-nbn
Total: 31 hits
CiteExportLink to record
Permanent link

Direct link
Cite
Citation style
  • apa
  • harvard1
  • ieee
  • modern-language-association-8th-edition
  • vancouver
  • Other style
More styles
Language
  • de-DE
  • en-GB
  • en-US
  • fi-FI
  • nn-NO
  • nn-NB
  • sv-SE
  • Other locale
More languages
Output format
  • html
  • text
  • asciidoc
  • rtf