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Bayesian Methods for Estimating Tool Position of an Industrial Manipulator
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.
2012 (English)In: Proceedings of Reglermöte 2012, 2012Conference paper, Published paper (Other academic)
Abstract [en]

State estimation of a flexible industrial manipulator is presented using experimental data. The problem is formulated in a Bayesian framework where the extended Kalman filter and particle filter are used. The filters use the joint positions on the motor side of the gearboxes as well as the acceleration at the end-effector as measurements and estimates the corresponding joint angles on the arm side of the gearboxes. The techniques are verified on a state of the art industrial robot, and it is shown that the use of the acceleration at the end-effector improves the estimates significantly.

Place, publisher, year, edition, pages
2012.
Keyword [sv]
Estimation, Extended Kalman filter, Particle filter, Accelerometer, Industrial robot
National Category
Control Engineering
Identifiers
URN: urn:nbn:se:liu:diva-88979OAI: oai:DiVA.org:liu-88979DiVA: diva2:606589
Conference
Reglermöte 2012, Uppsala, Sweden, 13-14 June, 2012
Projects
Vinnova Excellence Center LINK-SIC at Linköping University, SwedenSSF project Collaborative Localization
Funder
VinnovaSwedish Foundation for Strategic Research
Available from: 2013-02-19 Created: 2013-02-19 Last updated: 2013-07-10

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Authority records BETA

Axelsson, PatrikKarlsson, RickardNorrlöf, Mikael

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CiteExportLink to record
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Citation style
  • apa
  • harvard1
  • ieee
  • modern-language-association-8th-edition
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  • Other style
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Language
  • de-DE
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  • nn-NB
  • sv-SE
  • Other locale
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