Deutsch
 
Hilfe Datenschutzhinweis Impressum
  DetailsucheBrowse

Datensatz

DATENSATZ AKTIONENEXPORT
Zur Ablage hinzufügen
 Lokale TagsFreigabegeschichteDetailsÜbersicht
  Switched Latent Force Models for Movement Segmentation

Alvarez, M., Peters, J., Schölkopf, B., & Lawrence, N. (2011). Switched Latent Force Models for Movement Segmentation. Advances in Neural Information Processing Systems 23: 24th Annual Conference on Neural Information Processing Systems 2010, 55-63.

Item is

 

einblenden: alle ausblenden: alle

Basisdaten

einblenden: ausblenden:
Datensatz-Permalink: https://hdl.handle.net/11858/00-001M-0000-0013-BB86-F Versions-Permalink: https://hdl.handle.net/21.11116/0000-0002-0B09-9
Genre: Konferenzbeitrag

Externe Referenzen

einblenden:
ausblenden:
externe Referenz:
https://papers.nips.cc/paper/4001-switched-latent-force-models-for-movement-segmentation.pdf (Verlagsversion)
Beschreibung:
-
OA-Status:

Urheber

einblenden:
ausblenden:
 Urheber:
Alvarez, MA, Autor           
Peters, J1, 2, Autor           
Schölkopf, B1, 2, Autor           
Lawrence, ND, Autor
Affiliations:
1Department Empirical Inference, Max Planck Institute for Biological Cybernetics, Max Planck Society, ou_1497795              
2Max Planck Institute for Biological Cybernetics, Max Planck Society, Spemannstrasse 38, 72076 Tübingen, DE, ou_1497794              

Inhalt

einblenden:
ausblenden:
Schlagwörter: -
 Zusammenfassung: Latent force models encode the interaction between multiple related dynamical systems in the form of a kernel or covariance function. Each variable to be modeled is represented as the output of a differential equation and each differential equation is driven by a weighted sum of latent functions with uncertainty given by a Gaussian process prior. In this paper we consider employing the latent force model framework for the problem of determining robot motor primitives. To deal with discontinuities in the dynamical systems or the latent driving force we introduce an extension of the basic latent force model, that switches between different latent functions and potentially different dynamical systems. This creates a versatile representation for robot movements that can capture discrete changes and non-linearities in the dynamics. We give illustrative examples on both synthetic data and for striking movements recorded using a BarrettWAM robot as haptic input device. Our inspiration is robot motor primitives, but we expect our model to have wide application for dynamical systems including models for human motion capture data and systems biology.

Details

einblenden:
ausblenden:
Sprache(n):
 Datum: 2011-06
 Publikationsstatus: Erschienen
 Seiten: -
 Ort, Verlag, Ausgabe: -
 Inhaltsverzeichnis: -
 Art der Begutachtung: -
 Identifikatoren: BibTex Citekey: 6743
 Art des Abschluß: -

Veranstaltung

einblenden:
ausblenden:
Titel: Twenty-Fourth Annual Conference on Neural Information Processing Systems (NIPS 2010)
Veranstaltungsort: Vancouver, BC, Canada
Start-/Enddatum: 2010-12-06 - 2010-12-11

Entscheidung

einblenden:

Projektinformation

einblenden:

Quelle 1

einblenden:
ausblenden:
Titel: Advances in Neural Information Processing Systems 23: 24th Annual Conference on Neural Information Processing Systems 2010
Genre der Quelle: Zeitschrift
 Urheber:
Lafferty, J, Herausgeber
Williams, CKI, Herausgeber
Shawe-Taylor, J, Herausgeber
Zemel, RS, Herausgeber
Culotta, A, Herausgeber
Affiliations:
-
Ort, Verlag, Ausgabe: Red Hook, NY, USA : Curran
Seiten: - Band / Heft: - Artikelnummer: - Start- / Endseite: 55 - 63 Identifikator: ISBN: 978-1-617-82380-0