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Gesture Recognition Using Evolution Strategy Neural Network
Mälardalen University, School of Innovation, Design and Engineering.
Mälardalen University, School of Innovation, Design and Engineering.
Mälardalen University, School of Innovation, Design and Engineering.ORCID iD: 0000-0002-5224-8302
Mälardalen University, School of Innovation, Design and Engineering.ORCID iD: 0000-0001-5141-7242
2008 (English)In: 2008 IEEE INTERNATIONAL CONFERENCE ON EMERGING TECHNOLOGIES AND FACTORY AUTOMATION, PROCEEDINGS, 2008, p. 245-248Conference paper, Published paper (Refereed)
Abstract [en]

A new approach to interact with an industrial robot using hand gestures is presented. System proposed here can learn first time user's hand gestures rapidly. This improves product usability and acceptability. Artificial neural networks trained with the evolution strategy technique are found to be suited for this problem. The gesture recognition system is an integrated part of a larger project for addressing intelligent human-robot interaction using a novel multi-modal paradigm. The goal of the overall project is to address complexity issues related to robot programming by providing a multi-modal user friendly interacting system that can be used by SMEs.

Place, publisher, year, edition, pages
2008. p. 245-248
National Category
Engineering and Technology
Identifiers
URN: urn:nbn:se:mdh:diva-7277DOI: 10.1109/ETFA.2008.4638401ISI: 000260495500044Scopus ID: 2-s2.0-56349085101ISBN: 978-1-4244-1505-2 (print)OAI: oai:DiVA.org:mdh-7277DiVA, id: diva2:237287
Conference
13th IEEE International Conference on Emerging Technologies and Factory Automation Location: Hamburg, GERMANY Date: SEP 15-18, 2008
Available from: 2009-09-25 Created: 2009-09-25 Last updated: 2013-12-19Bibliographically approved

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Çürüklü, BaranAsplund, Lars

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Total: 46 hits
CiteExportLink to record
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Citation style
  • apa
  • ieee
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  • de-DE
  • en-GB
  • en-US
  • fi-FI
  • nn-NO
  • nn-NB
  • sv-SE
  • Other locale
More languages
Output format
  • html
  • text
  • asciidoc
  • rtf