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Teleoperation for a ball-catching task with significant dynamics
KTH, School of Computer Science and Communication (CSC), Centres, Centre for Autonomous Systems, CAS.ORCID iD: 0000-0003-2078-8854
KTH, School of Computer Science and Communication (CSC), Centres, Centre for Autonomous Systems, CAS.
KTH, School of Computer Science and Communication (CSC), Centres, Centre for Autonomous Systems, CAS.
2008 (English)In: Neural Networks, ISSN 0893-6080, E-ISSN 1879-2782, Vol. 21, no 4, 604-620 p.Article in journal (Refereed) Published
Abstract [en]

In this paper we present ongoing work on how to incorporate human motion models into the design of a high performance teleoperation platform. A short description of human motion models used for ball-catching is followed by a more detailed study of a teleoperation platform on which to conduct experiments. Also, a pilot study using minimum jerk theory to explain user input behavior in teleoperated catching is presented.

Place, publisher, year, edition, pages
Elsevier, 2008. Vol. 21, no 4, 604-620 p.
Keyword [en]
teleoperation, control, high performance manipulation, human motion
National Category
Computer and Information Science
Identifiers
URN: urn:nbn:se:kth:diva-34165DOI: 10.1016/j.neunet.2008.03.011ISI: 000257639800006Scopus ID: 2-s2.0-44949177276OAI: oai:DiVA.org:kth-34165DiVA: diva2:419991
Note
NOTICE: this is the author’s version of a work that was accepted for publication in Neural Networks. Changes resulting from the publishing process, such as peer review, editing, corrections, structural formatting, and other quality control mechanisms may not be reflected in this document. Changes may have been made to this work since it was submitted for publication. A definitive version was subsequently published in Neural Networks, VOL 21, ISSUE 4, May 2008 DOI: 10.1016/j.neunet.2008.04.002 QC 20110530Available from: 2011-12-20 Created: 2011-05-27 Last updated: 2011-12-20Bibliographically approved

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