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Efficient Trajectory Reshaping in a Dynamic Environment
Royal Inst Technol, Sweden.
Linköping University, Department of Electrical Engineering, Automatic Control. Linköping University, Faculty of Science & Engineering. ABB AB, Sweden.
2018 (English)In: 2018 IEEE 15TH INTERNATIONAL WORKSHOP ON ADVANCED MOTION CONTROL (AMC), IEEE , 2018, p. 54-59Conference paper, Published paper (Refereed)
Abstract [en]

A general trajectory planner for optimal control problems is presented and applied to a robot system. The approach is based on timed elastic bands and nonlinear model predictive control. By exploiting the sparsity in the underlying optimization problems the computational effort can be significantly reduced, resulting in a real-time capable planner. In addition, a localization based switching strategy is employed to enforce convergence and stability. The planning procedure is illustrated in a robotics application using a realistic SCARA type robot.

Place, publisher, year, edition, pages
IEEE , 2018. p. 54-59
Series
International Workshop on Advanced Motion Control, ISSN 1943-6572
National Category
Robotics
Identifiers
URN: urn:nbn:se:liu:diva-150314DOI: 10.1109/AMC.2019.8371062ISI: 000436348700007ISBN: 978-1-5386-1946-9 (print)OAI: oai:DiVA.org:liu-150314DiVA, id: diva2:1239455
Conference
15th IEEE International Workshop on Advanced Motion Control (AMC)
Note

Funding Agencies|VINNOVA industrial excelence center LINK-SIC at Linkoping University; KTH initiative, digitalization of Swedish industry

Available from: 2018-08-16 Created: 2018-08-16 Last updated: 2018-09-11

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Norrlöf, Mikael
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Total: 77 hits
CiteExportLink to record
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Cite
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
  • html
  • text
  • asciidoc
  • rtf