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Grasp recognition by time-clustering, fuzzy modeling, and Hidden Markov Models (HMM): a comparative study
Örebro University, School of Science and Technology. (AASS)
Örebro University, School of Science and Technology. (AASS)
2008 (English)In: IEEE international conference on fuzzy systems, FUZZ-IEEE 2008. (IEEE World Congress on Computational Intelligence), NewYork: IEEE , 2008, 599-605 p.Conference paper, (Refereed)
Abstract [en]

This paper deals with three different methodsfor grasp recognition for a human hand. Grasp recognitionis a major part of the approach for Programming-by-Demonstration (PbD) for five-fingered robotic hands. A humanoperator instructs the robot to perform different grasps wearinga data glove. For a number of human grasps, the finger jointangle trajectories are recorded and modeled by fuzzy clusteringand Takagi-Sugeno modeling. This leads to grasp models usingthe time as input parameter and the joint angles as outputs.Given a test grasp by the human operator the robot classifiesand recognizes the grasp and generates the corresponding robotgrasp. Three methods for grasp recognition are presented andcompared. In the first method the test grasp is comparedwith model grasps using the difference between the modeloutputs. In the second one, qualitative fuzzy models are usedfor recognition and classification. The third method is based onHidden-Markov-Models (HMM) which are commonly used inrobot learning

Place, publisher, year, edition, pages
NewYork: IEEE , 2008. 599-605 p.
Keyword [en]
grasp recognition, Programming-by-Demonstration
National Category
Computer Science
Research subject
Computer and Systems Science
Identifiers
URN: urn:nbn:se:oru:diva-8430DOI: 10.1109/FUZZY.2008.4630430ISBN: 978-1-4244-1818-3 (print)OAI: oai:DiVA.org:oru-8430DiVA: diva2:274832
Conference
IEEE international conference on fuzzy systems, FUZZ-IEEE 2008, 1-6 June, Hong Kong
Available from: 2009-11-02 Created: 2009-11-02 Last updated: 2011-03-18Bibliographically approved

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CiteExportLink to record
Permanent link

Direct link
Cite
Citation style
  • apa
  • harvard1
  • ieee
  • modern-language-association-8th-edition
  • vancouver
  • 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