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Maximum likelihood point cloud acquisition from a mobile platform
Örebro University, School of Science and Technology. (AASS Learning Systems Lab)ORCID iD: 0000-0002-6013-4874
Örebro University, School of Science and Technology. (AASS Learning Systems Lab)ORCID iD: 0000-0003-0217-9326
2009 (English)In: International conference on advanced robotics, ICAR 2009., New York: IEEE conference proceedings, 2009, 1-6 p.Conference paper, (Refereed)
Abstract [en]

This paper describes an approach to acquire locally consistent range data scans from a moving sensor platform. Data from a vertically mounted rotating laser scanner and odometry position estimates are fused and used to estimate maximum likelihood point clouds. An estimation algorithm is applied to reduce the accumulated error after a full rotation of the range finder. A configuration consisting of a SICK laser scanner mounted on a rotational actuator is described and used to evaluate the proposed approach. The data sets analyzed suggest a significant improvement in point cloud consistency, even over a short travel distance.

Place, publisher, year, edition, pages
New York: IEEE conference proceedings, 2009. 1-6 p.
National Category
Engineering and Technology Other Computer and Information Science
Research subject
Computer and Systems Science
Identifiers
URN: urn:nbn:se:oru:diva-8442ISI: 000270815500075Scopus ID: 2-s2.0-70449368985ISBN: 978-1-4244-4855-5 (print)OAI: oai:DiVA.org:oru-8442DiVA: diva2:274893
Conference
IEEE international conference on advanced robotics (ICAR), 22-26 June 2009, Munic
Available from: 2009-11-09 Created: 2009-11-02 Last updated: 2017-03-16Bibliographically approved

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Stoyanov, TodorLilienthal, Achim J.
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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