Dynamics identification for enhanced haptic display in VR based training platforms
Identifieur interne : 000E73 ( PascalFrancis/Checkpoint ); précédent : 000E72; suivant : 000E74Dynamics identification for enhanced haptic display in VR based training platforms
Auteurs : D. Bi [Hong Kong] ; Y. F. Li [Hong Kong] ; G. L. Wang [Hong Kong]Source :
- SPIE proceedings series [ 1017-2653 ] ; 2003.
Descripteurs français
- Pascal (Inist)
- Wicri :
- topic : Réalité virtuelle.
English descriptors
Abstract
Current VR systems mainly use geometric models, which has proved to be insufficient to provide the haptic display capability needed in many applications such as surgery training. Physics based dynamic models play a crucial role in this respect, e.g. for realistic haptic display of the operating feel via Virtual Reality (VR) systems. Such physics based models are desirably obtained via experimental identification. However, traditional dynamics identification methods normally require very large sized training data sets, which maybe difficult to meet in practical applications. This paper presents a method for identifying dynamics models using Support Vector Machines (SVM) regression algorithm which is more effective than traditional methods for high dimensional sparse training data. This method can be used as a generic learning machine or as a special learning technique that can make full use of the known dynamics structure knowledge. The experimental results show the application of our method identifying friction models for realistic haptic display.
Affiliations:
Links toward previous steps (curation, corpus...)
Links to Exploration step
Pascal:03-0482265Le document en format XML
<record><TEI><teiHeader><fileDesc><titleStmt><title xml:lang="en" level="a">Dynamics identification for enhanced haptic display in VR based training platforms</title>
<author><name sortKey="Bi, D" sort="Bi, D" uniqKey="Bi D" first="D." last="Bi">D. Bi</name>
<affiliation wicri:level="1"><inist:fA14 i1="01"><s1>Department of Manufacturing Engineering and Engineering Management City University of Hong Kong</s1>
<s2>Kowloon</s2>
<s3>HKG</s3>
<sZ>1 aut.</sZ>
<sZ>2 aut.</sZ>
<sZ>3 aut.</sZ>
</inist:fA14>
<country>Hong Kong</country>
<wicri:noRegion>Department of Manufacturing Engineering and Engineering Management City University of Hong Kong</wicri:noRegion>
</affiliation>
</author>
<author><name sortKey="Li, Y F" sort="Li, Y F" uniqKey="Li Y" first="Y. F." last="Li">Y. F. Li</name>
<affiliation wicri:level="1"><inist:fA14 i1="01"><s1>Department of Manufacturing Engineering and Engineering Management City University of Hong Kong</s1>
<s2>Kowloon</s2>
<s3>HKG</s3>
<sZ>1 aut.</sZ>
<sZ>2 aut.</sZ>
<sZ>3 aut.</sZ>
</inist:fA14>
<country>Hong Kong</country>
<wicri:noRegion>Department of Manufacturing Engineering and Engineering Management City University of Hong Kong</wicri:noRegion>
</affiliation>
</author>
<author><name sortKey="Wang, G L" sort="Wang, G L" uniqKey="Wang G" first="G. L." last="Wang">G. L. Wang</name>
<affiliation wicri:level="1"><inist:fA14 i1="01"><s1>Department of Manufacturing Engineering and Engineering Management City University of Hong Kong</s1>
<s2>Kowloon</s2>
<s3>HKG</s3>
<sZ>1 aut.</sZ>
<sZ>2 aut.</sZ>
<sZ>3 aut.</sZ>
</inist:fA14>
<country>Hong Kong</country>
<wicri:noRegion>Department of Manufacturing Engineering and Engineering Management City University of Hong Kong</wicri:noRegion>
</affiliation>
</author>
</titleStmt>
<publicationStmt><idno type="wicri:source">INIST</idno>
<idno type="inist">03-0482265</idno>
<date when="2003">2003</date>
<idno type="stanalyst">PASCAL 03-0482265 INIST</idno>
<idno type="RBID">Pascal:03-0482265</idno>
<idno type="wicri:Area/PascalFrancis/Corpus">001137</idno>
<idno type="wicri:Area/PascalFrancis/Curation">000374</idno>
<idno type="wicri:Area/PascalFrancis/Checkpoint">000E73</idno>
</publicationStmt>
<sourceDesc><biblStruct><analytic><title xml:lang="en" level="a">Dynamics identification for enhanced haptic display in VR based training platforms</title>
<author><name sortKey="Bi, D" sort="Bi, D" uniqKey="Bi D" first="D." last="Bi">D. Bi</name>
<affiliation wicri:level="1"><inist:fA14 i1="01"><s1>Department of Manufacturing Engineering and Engineering Management City University of Hong Kong</s1>
<s2>Kowloon</s2>
<s3>HKG</s3>
<sZ>1 aut.</sZ>
<sZ>2 aut.</sZ>
<sZ>3 aut.</sZ>
</inist:fA14>
<country>Hong Kong</country>
<wicri:noRegion>Department of Manufacturing Engineering and Engineering Management City University of Hong Kong</wicri:noRegion>
</affiliation>
</author>
<author><name sortKey="Li, Y F" sort="Li, Y F" uniqKey="Li Y" first="Y. F." last="Li">Y. F. Li</name>
<affiliation wicri:level="1"><inist:fA14 i1="01"><s1>Department of Manufacturing Engineering and Engineering Management City University of Hong Kong</s1>
<s2>Kowloon</s2>
<s3>HKG</s3>
<sZ>1 aut.</sZ>
<sZ>2 aut.</sZ>
<sZ>3 aut.</sZ>
</inist:fA14>
<country>Hong Kong</country>
<wicri:noRegion>Department of Manufacturing Engineering and Engineering Management City University of Hong Kong</wicri:noRegion>
</affiliation>
</author>
<author><name sortKey="Wang, G L" sort="Wang, G L" uniqKey="Wang G" first="G. L." last="Wang">G. L. Wang</name>
<affiliation wicri:level="1"><inist:fA14 i1="01"><s1>Department of Manufacturing Engineering and Engineering Management City University of Hong Kong</s1>
<s2>Kowloon</s2>
<s3>HKG</s3>
<sZ>1 aut.</sZ>
<sZ>2 aut.</sZ>
<sZ>3 aut.</sZ>
</inist:fA14>
<country>Hong Kong</country>
<wicri:noRegion>Department of Manufacturing Engineering and Engineering Management City University of Hong Kong</wicri:noRegion>
</affiliation>
</author>
</analytic>
<series><title level="j" type="main">SPIE proceedings series</title>
<idno type="ISSN">1017-2653</idno>
<imprint><date when="2003">2003</date>
</imprint>
</series>
</biblStruct>
</sourceDesc>
<seriesStmt><title level="j" type="main">SPIE proceedings series</title>
<idno type="ISSN">1017-2653</idno>
</seriesStmt>
</fileDesc>
<profileDesc><textClass><keywords scheme="KwdEn" xml:lang="en"><term>Haptic interfaces</term>
<term>Physical model</term>
<term>Vector support machine</term>
<term>Virtual reality</term>
</keywords>
<keywords scheme="Pascal" xml:lang="fr"><term>Réalité virtuelle</term>
<term>Interface haptique</term>
<term>Modèle physique</term>
<term>Identification dynamique</term>
<term>Affichage haptique</term>
<term>Machine support vecteur</term>
</keywords>
<keywords scheme="Wicri" type="topic" xml:lang="fr"><term>Réalité virtuelle</term>
</keywords>
</textClass>
</profileDesc>
</teiHeader>
<front><div type="abstract" xml:lang="en">Current VR systems mainly use geometric models, which has proved to be insufficient to provide the haptic display capability needed in many applications such as surgery training. Physics based dynamic models play a crucial role in this respect, e.g. for realistic haptic display of the operating feel via Virtual Reality (VR) systems. Such physics based models are desirably obtained via experimental identification. However, traditional dynamics identification methods normally require very large sized training data sets, which maybe difficult to meet in practical applications. This paper presents a method for identifying dynamics models using Support Vector Machines (SVM) regression algorithm which is more effective than traditional methods for high dimensional sparse training data. This method can be used as a generic learning machine or as a special learning technique that can make full use of the known dynamics structure knowledge. The experimental results show the application of our method identifying friction models for realistic haptic display.</div>
</front>
</TEI>
<inist><standard h6="B"><pA><fA01 i1="01" i2="1"><s0>1017-2653</s0>
</fA01>
<fA05><s2>4756</s2>
</fA05>
<fA08 i1="01" i2="1" l="ENG"><s1>Dynamics identification for enhanced haptic display in VR based training platforms</s1>
</fA08>
<fA09 i1="01" i2="1" l="ENG"><s1>Virtual reality and its application in industry : Hangzhou, 9-12 April 2002</s1>
</fA09>
<fA11 i1="01" i2="1"><s1>BI (D.)</s1>
</fA11>
<fA11 i1="02" i2="1"><s1>LI (Y. F.)</s1>
</fA11>
<fA11 i1="03" i2="1"><s1>WANG (G. L.)</s1>
</fA11>
<fA12 i1="01" i2="1"><s1>ZHIGENG PAN</s1>
<s9>ed.</s9>
</fA12>
<fA12 i1="02" i2="1"><s1>JIAOYING SHI</s1>
<s9>ed.</s9>
</fA12>
<fA14 i1="01"><s1>Department of Manufacturing Engineering and Engineering Management City University of Hong Kong</s1>
<s2>Kowloon</s2>
<s3>HKG</s3>
<sZ>1 aut.</sZ>
<sZ>2 aut.</sZ>
<sZ>3 aut.</sZ>
</fA14>
<fA18 i1="01" i2="1"><s1>International Society for Optical Engineering</s1>
<s2>Bellingham WA</s2>
<s3>USA</s3>
<s9>patr.</s9>
</fA18>
<fA20><s1>129-136</s1>
</fA20>
<fA21><s1>2003</s1>
</fA21>
<fA23 i1="01"><s0>ENG</s0>
</fA23>
<fA26 i1="01"><s0>0-8194-4519-3</s0>
</fA26>
<fA43 i1="01"><s1>INIST</s1>
<s2>21760</s2>
<s5>354000117369730170</s5>
</fA43>
<fA44><s0>0000</s0>
<s1>© 2003 INIST-CNRS. All rights reserved.</s1>
</fA44>
<fA45><s0>14 ref.</s0>
</fA45>
<fA47 i1="01" i2="1"><s0>03-0482265</s0>
</fA47>
<fA60><s1>P</s1>
<s2>C</s2>
</fA60>
<fA61><s0>A</s0>
</fA61>
<fA64 i1="01" i2="1"><s0>SPIE proceedings series</s0>
</fA64>
<fA66 i1="01"><s0>USA</s0>
</fA66>
<fC01 i1="01" l="ENG"><s0>Current VR systems mainly use geometric models, which has proved to be insufficient to provide the haptic display capability needed in many applications such as surgery training. Physics based dynamic models play a crucial role in this respect, e.g. for realistic haptic display of the operating feel via Virtual Reality (VR) systems. Such physics based models are desirably obtained via experimental identification. However, traditional dynamics identification methods normally require very large sized training data sets, which maybe difficult to meet in practical applications. This paper presents a method for identifying dynamics models using Support Vector Machines (SVM) regression algorithm which is more effective than traditional methods for high dimensional sparse training data. This method can be used as a generic learning machine or as a special learning technique that can make full use of the known dynamics structure knowledge. The experimental results show the application of our method identifying friction models for realistic haptic display.</s0>
</fC01>
<fC02 i1="01" i2="X"><s0>001D02C06</s0>
</fC02>
<fC03 i1="01" i2="X" l="FRE"><s0>Réalité virtuelle</s0>
<s5>01</s5>
</fC03>
<fC03 i1="01" i2="X" l="ENG"><s0>Virtual reality</s0>
<s5>01</s5>
</fC03>
<fC03 i1="01" i2="X" l="SPA"><s0>Realidad virtual</s0>
<s5>01</s5>
</fC03>
<fC03 i1="02" i2="1" l="FRE"><s0>Interface haptique</s0>
<s5>02</s5>
</fC03>
<fC03 i1="02" i2="1" l="ENG"><s0>Haptic interfaces</s0>
<s5>02</s5>
</fC03>
<fC03 i1="03" i2="X" l="FRE"><s0>Modèle physique</s0>
<s5>03</s5>
</fC03>
<fC03 i1="03" i2="X" l="ENG"><s0>Physical model</s0>
<s5>03</s5>
</fC03>
<fC03 i1="03" i2="X" l="SPA"><s0>Modelo físico</s0>
<s5>03</s5>
</fC03>
<fC03 i1="04" i2="X" l="FRE"><s0>Identification dynamique</s0>
<s4>INC</s4>
<s5>82</s5>
</fC03>
<fC03 i1="05" i2="X" l="FRE"><s0>Affichage haptique</s0>
<s4>INC</s4>
<s5>83</s5>
</fC03>
<fC03 i1="06" i2="X" l="FRE"><s0>Machine support vecteur</s0>
<s4>CD</s4>
<s5>96</s5>
</fC03>
<fC03 i1="06" i2="X" l="ENG"><s0>Vector support machine</s0>
<s4>CD</s4>
<s5>96</s5>
</fC03>
<fN21><s1>328</s1>
</fN21>
<fN82><s1>PSI</s1>
</fN82>
</pA>
<pR><fA30 i1="01" i2="1" l="ENG"><s1>International conference on virtual reality and its application in industry</s1>
<s3>Hangzhou CHN</s3>
<s4>2002-04-09</s4>
</fA30>
</pR>
</standard>
</inist>
<affiliations><list><country><li>Hong Kong</li>
</country>
</list>
<tree><country name="Hong Kong"><noRegion><name sortKey="Bi, D" sort="Bi, D" uniqKey="Bi D" first="D." last="Bi">D. Bi</name>
</noRegion>
<name sortKey="Li, Y F" sort="Li, Y F" uniqKey="Li Y" first="Y. F." last="Li">Y. F. Li</name>
<name sortKey="Wang, G L" sort="Wang, G L" uniqKey="Wang G" first="G. L." last="Wang">G. L. Wang</name>
</country>
</tree>
</affiliations>
</record>
Pour manipuler ce document sous Unix (Dilib)
EXPLOR_STEP=$WICRI_ROOT/Ticri/CIDE/explor/HapticV1/Data/PascalFrancis/Checkpoint
HfdSelect -h $EXPLOR_STEP/biblio.hfd -nk 000E73 | SxmlIndent | more
Ou
HfdSelect -h $EXPLOR_AREA/Data/PascalFrancis/Checkpoint/biblio.hfd -nk 000E73 | SxmlIndent | more
Pour mettre un lien sur cette page dans le réseau Wicri
{{Explor lien |wiki= Ticri/CIDE |area= HapticV1 |flux= PascalFrancis |étape= Checkpoint |type= RBID |clé= Pascal:03-0482265 |texte= Dynamics identification for enhanced haptic display in VR based training platforms }}
![]() | This area was generated with Dilib version V0.6.23. | ![]() |