DocumentCode :
2596894
Title :
Force skill training with a hybrid trainer model
Author :
Esen, Hasan ; Ichi Yano, Ken ; Buss, Martin
Author_Institution :
Inst. of Autom. Control Eng., Tech. Univ. Munchen, Munich
fYear :
2008
fDate :
1-3 Aug. 2008
Firstpage :
9
Lastpage :
14
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.
Keywords :
control engineering computing; force control; learning (artificial intelligence); position control; virtual reality; bone drilling training application; force skill training; hybrid trainer model; n dimensional Euclidean distances; objective evaluation method; weighted k-means algorithm; Bones; Drilling; Force control; Force feedback; Force sensors; Haptic interfaces; Humans; Springs; Testing; Virtual reality;
fLanguage :
English
Publisher :
ieee
Conference_Titel :
Robot and Human Interactive Communication, 2008. RO-MAN 2008. The 17th IEEE International Symposium on
Conference_Location :
Munich
Print_ISBN :
978-1-4244-2212-8
Electronic_ISBN :
978-1-4244-2213-5
Type :
conf
DOI :
10.1109/ROMAN.2008.4600635
Filename :
4600635
Link To Document :
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