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Position Estimation and Modeling of a Flexible Industrial Robot
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.
2005 (English)In: Proceedings of the 16th IFAC World Congress, 2005, 1311-1311 p.Conference paper, Published paper (Refereed)
Abstract [en]

A sensor fusion technique is presented and it is shown to achieve good estimates of the position for a 3 degrees-of-freedom industrial robot model. By using an accelerometer the estimate of the tool position accuracy can be improved. The computation of the position is formulated as a Bayesian estimation problem and two solutions are proposed. One using the extended Kalman filter and one using the particle filter. Since the aim is to use the positions estimates to improve trajectory tracking with an iterative learning control method, no computational constraints arise. In an extensive simulation study the performance is compared to the Cramér-Rao lower bound. A significant improvement in position accuracy is achieved using the sensor fusion technique.

Place, publisher, year, edition, pages
2005. 1311-1311 p.
Keyword [en]
Industrial robots, Estimation, Extended Kalman filter, Estimation algorithms
National Category
Engineering and Technology Control Engineering
Identifiers
URN: urn:nbn:se:liu:diva-29531DOI: 10.3182/20050703-6-CZ-1902.01312Local ID: 14889ISBN: 978-3-902661-75-3 (print)OAI: oai:DiVA.org:liu-29531DiVA: diva2:250346
Conference
16th IFAC World Congress, Prague, Czech Republic, July, 2005
Available from: 2009-10-09 Created: 2009-10-09 Last updated: 2013-04-16

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Karlsson, RickardNorrlöf, Mikael

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Citation style
  • apa
  • harvard1
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  • modern-language-association-8th-edition
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  • Other style
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Language
  • de-DE
  • en-GB
  • en-US
  • fi-FI
  • nn-NO
  • nn-NB
  • sv-SE
  • Other locale
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Output format
  • html
  • text
  • asciidoc
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