oru.sePublications
Change search
CiteExportLink to record
Permanent link

Direct link
Cite
Citation style
  • apa
  • 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
Scan registration for autonomous mining vehicles using 3D-NDT
Örebro University, Department of Technology. (AASS)ORCID iD: 0000-0001-8658-2985
Örebro University, Department of Technology. (AASS)ORCID iD: 0000-0003-0217-9326
Department of Computing and Informatics, University of Lincoln, Lincoln, United Kingdom. (Department of Computing and Informatics)
2007 (English)In: Journal of Field Robotics, ISSN 1556-4959, E-ISSN 1556-4967, Vol. 24, no 10, p. 803-827Article in journal (Refereed) Published
Abstract [en]

Scan registration is an essential sub-task when building maps based on range finder data from mobile robots. The problem is to deduce how the robot has moved between consecutive scans, based on the shape of overlapping portions of the scans. This paper presents a new algorithm for registration of 3D data. The algorithm is a generalisation and improvement of the normal distributions transform (NDT) for 2D data developed by Biber and Straßer, which allows for accurate registration using a memory-efficient representation of the scan surface. A detailed quantitative and qualitative comparison of the new algorithm with the 3D version of the popular ICP (iterative closest point) algorithm is presented. Results with actual mine data, some of which were collected with a new prototype 3D laser scanner, show that the presented algorithm is faster and slightly more reliable than the standard ICP algorithm for 3D registration, while using a more memory-efficient scan surface representation.

Place, publisher, year, edition, pages
Hoboken, N.J., USA: John Wiley & Sons, 2007. Vol. 24, no 10, p. 803-827
National Category
Engineering and Technology Computer and Information Sciences
Research subject
Computer and Systems Science
Identifiers
URN: urn:nbn:se:oru:diva-4258DOI: 10.1002/rob.20204ISI: 000250768000002Scopus ID: 2-s2.0-34247125634OAI: oai:DiVA.org:oru-4258DiVA, id: diva2:138557
Note

Special issue on mining robotics.

Available from: 2008-11-13 Created: 2008-11-13 Last updated: 2018-06-12Bibliographically approved

Open Access in DiVA

Scan Registration for Autonomous Mining Vehicles Using 3D-NDT(1031 kB)23 downloads
File information
File name FULLTEXT01.pdfFile size 1031 kBChecksum SHA-512
dc1cfa76bf7929682884e3b5c6c14f2270855a8b155a8032e7bf637a2c64edb42f01d3eb32106de9e8c7b3e25d3e3e5b079bc753b9d62e5a4c50e540c4351c89
Type fulltextMimetype application/pdf

Other links

Publisher's full textScopus

Authority records BETA

Magnusson, MartinLilienthal, Achim J.

Search in DiVA

By author/editor
Magnusson, MartinLilienthal, Achim J.
By organisation
Department of Technology
In the same journal
Journal of Field Robotics
Engineering and TechnologyComputer and Information Sciences

Search outside of DiVA

GoogleGoogle Scholar
Total: 23 downloads
The number of downloads is the sum of all downloads of full texts. It may include eg previous versions that are now no longer available

doi
urn-nbn

Altmetric score

doi
urn-nbn
Total: 383 hits
CiteExportLink to record
Permanent link

Direct link
Cite
Citation style
  • apa
  • 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