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Particle Filter SLAM with High Dimensional Vehicle Model
Linköping University, Department of Electrical Engineering, Automatic Control. Linköping University, The Institute of Technology.
Linköping University, Department of Electrical Engineering, Automatic Control. Linköping University, The Institute of Technology.
Linköping University, Department of Electrical Engineering, Automatic Control. Linköping University, The Institute of Technology.
Linköping University, Department of Electrical Engineering, Automatic Control. Linköping University, The Institute of Technology.
2008 (English)Report (Other academic)
Abstract [en]

This work presents a particle filter (PF) method closely related to FastSLAM for solving the simultaneous localization and mapping (SLAM) problem. Using the standard FastSLAM algorithm, only low-dimensional vehicle models can be handled due to computational constraints. In this work an extra factorization of the problem is introduced that makes high-dimensional vehicle models computationally feasible. Results using experimental data from a UAV (helicopter) are presented. The algorithm fuses measurements from on-board inertial sensors (accelerometer and gyro), barometer, and vision in order to solve the SLAM problem.

Place, publisher, year, edition, pages
Linköping: Linköping University Electronic Press, 2008. , 21 p.
Series
LiTH-ISY-R, ISSN 1400-3902 ; 2863
Keyword [en]
Rao-Blackwellized/marginalized particle lter, sensor fusion, simultaneous localization and mapping, inertial sensors, UAV, vision.
National Category
Control Engineering
Identifiers
URN: urn:nbn:se:liu:diva-56186ISRN: LiTH-ISY-R-2863OAI: oai:DiVA.org:liu-56186DiVA: diva2:316985
Available from: 2010-04-30 Created: 2010-04-30 Last updated: 2014-10-01Bibliographically approved

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Authority records BETA

Törnqvist, DavidSchön, ThomasKarlsson, RickardGustafsson, Fredrik

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Törnqvist, DavidSchön, ThomasKarlsson, RickardGustafsson, Fredrik
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CiteExportLink to record
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Citation style
  • apa
  • harvard1
  • ieee
  • modern-language-association-8th-edition
  • vancouver
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  • 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
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  • asciidoc
  • rtf