Force skill training with a hybrid trainer model

Hasan Esen, Ke N.Ichi Yano, Martin Buss

Publikation: Beitrag in Buch/Bericht/KonferenzbandKonferenzbeitragBegutachtung

5 Zitate (Scopus)

Abstract

In this work, we present novel VR training strategies that incorporate a hybrid trainer model to train force. For modeling the trainer skill, weighted K-means algorithm in parameter space with LS optimization is implemented. The efficiency of the training strategies is verified via user tests in frame of a bone drilling training application. An objective evaluation method based on n dimensional Euclidean distances is introduced to assess user tests results. It is shown that the proposed strategies improve the student skill and accelerate force learning.

OriginalspracheEnglisch
TitelProceedings of the 17th IEEE International Symposium on Robot and Human Interactive Communication, RO-MAN
Seiten9-14
Seitenumfang6
DOIs
PublikationsstatusVeröffentlicht - 2008
Veranstaltung17th IEEE International Symposium on Robot and Human Interactive Communication, RO-MAN - Munich, Deutschland
Dauer: 1 Aug. 20083 Aug. 2008

Publikationsreihe

NameProceedings of the 17th IEEE International Symposium on Robot and Human Interactive Communication, RO-MAN

Konferenz

Konferenz17th IEEE International Symposium on Robot and Human Interactive Communication, RO-MAN
Land/GebietDeutschland
OrtMunich
Zeitraum1/08/083/08/08

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