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Where am I?: An NDT-based prior for MCL
Örebro University, School of Science and Technology. (AASS)ORCID iD: 0000-0002-9503-0602
Örebro University, School of Science and Technology. (AASS)ORCID iD: 0000-0001-8658-2985
Örebro University, School of Science and Technology. (AASS)ORCID iD: 0000-0003-0217-9326
2015 (English)In: 2015 European Conference on Mobile Robots (ECMR), New York: IEEE conference proceedings , 2015Conference paper, Published paper (Refereed)
Abstract [en]

One of the key requirements of autonomous mobile robots is a robust and accurate localisation system. Recent advances in the development of Monte Carlo Localisation (MCL) algorithms, especially the Normal Distribution Transform Monte Carlo Localisation (NDT-MCL), provides memory-efficient reliable localisation with industry-grade precision. We propose an approach for building an informed prior for NDT-MCL (in fact for any MCL algorithm) using an initial observation of the environment and its map. Leveraging on the NDT map representation, we build a set of poses using partial observations. After that we construct a Gaussian Mixture Model (GMM) over it. Next we obtain scores for each distribution in GMM. In this way we obtain in an efficient way a prior for NDT-MCL. Our approach provides a more focused then uniform initial distribution, concentrated in states where the robot is more likely to be, by building a Gaussian mixture model over potential poses. We present evaluations and quantitative results using real-world data from an indoor environment. Our experiments show that, compared to a uniform prior, the proposed method significantly increases the number of successful initialisations of NDT-MCL and reduces the time until convergence, at a negligible initial cost for computing the prior.

Place, publisher, year, edition, pages
New York: IEEE conference proceedings , 2015.
National Category
Computer Science
Research subject
Computer Science
Identifiers
URN: urn:nbn:se:oru:diva-51942DOI: 10.1109/ECMR.2015.7324175ISI: 000380213600010Scopus ID: 2-s2.0-84962243582ISBN: 978-1-4673-9163-4 (print)OAI: oai:DiVA.org:oru-51942DiVA: diva2:957495
Conference
7th European Conference on Mobile Robots, Lincoln, England, September 2-4, 2015
Projects
SPENCER
Funder
EU, FP7, Seventh Framework Programme, ICT-2011- 600877
Available from: 2016-09-02 Created: 2016-09-02 Last updated: 2017-10-18Bibliographically approved

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Kucner, Tomasz PiotrMagnusson, MartinLilienthal, Achim J.
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CiteExportLink to record
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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
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Output format
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  • asciidoc
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