Data-Driven Haptic Modeling and Rendering of Viscoelastic and Frictional Responses of Deformable Objects.
Identifieur interne : 000128 ( PubMed/Checkpoint ); précédent : 000127; suivant : 000129Data-Driven Haptic Modeling and Rendering of Viscoelastic and Frictional Responses of Deformable Objects.
Auteurs : Sunghoon Yim ; Seokhee Jeon ; Seungmoon ChoiSource :
- IEEE transactions on haptics [ 2329-4051 ] ; 2016.
Abstract
In this paper, we present an extended data-driven haptic rendering method capable of reproducing force responses during pushing and sliding interaction on a large surface area. The main part of the approach is a novel input variable set for the training of an interpolation model, which incorporates the position of a proxy - an imaginary contact point on the undeformed surface. This allows us to estimate friction in both sliding and sticking states in a unified framework. Estimating the proxy position is done in real-time based on simulation using a sliding yield surface - a surface defining a border between the sliding and sticking regions in the external force space. During modeling, the sliding yield surface is first identified via an automated palpation procedure. Then, through manual palpation on a target surface, input data and resultant force data are acquired. The data are used to build a radial basis interpolation model. During rendering, this input-output mapping interpolation model is used to estimate force responses in real-time in accordance with the interaction input. Physical performance evaluation demonstrates that our approach achieves reasonably high estimation accuracy. A user study also shows plausible perceptual realism under diverse and extensive exploration.
DOI: 10.1109/TOH.2016.2571690
PubMed: 27244750
Affiliations:
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The main part of the approach is a novel input variable set for the training of an interpolation model, which incorporates the position of a proxy - an imaginary contact point on the undeformed surface. This allows us to estimate friction in both sliding and sticking states in a unified framework. Estimating the proxy position is done in real-time based on simulation using a sliding yield surface - a surface defining a border between the sliding and sticking regions in the external force space. During modeling, the sliding yield surface is first identified via an automated palpation procedure. Then, through manual palpation on a target surface, input data and resultant force data are acquired. The data are used to build a radial basis interpolation model. During rendering, this input-output mapping interpolation model is used to estimate force responses in real-time in accordance with the interaction input. Physical performance evaluation demonstrates that our approach achieves reasonably high estimation accuracy. A user study also shows plausible perceptual realism under diverse and extensive exploration.</div></front></TEI><pubmed><MedlineCitation Status="Publisher" Owner="NLM"><PMID Version="1">27244750</PMID><DateCreated><Year>2016</Year><Month>5</Month><Day>31</Day></DateCreated><DateRevised><Year>2016</Year><Month>5</Month><Day>31</Day></DateRevised><Article PubModel="Print-Electronic"><Journal><ISSN IssnType="Electronic">2329-4051</ISSN><JournalIssue CitedMedium="Internet"><PubDate><Year>2016</Year><Month>May</Month><Day>23</Day></PubDate></JournalIssue><Title>IEEE transactions on haptics</Title><ISOAbbreviation>IEEE Trans Haptics</ISOAbbreviation></Journal><ArticleTitle>Data-Driven Haptic Modeling and Rendering of Viscoelastic and Frictional Responses of Deformable Objects.</ArticleTitle><Pagination><MedlinePgn></MedlinePgn></Pagination><Abstract><AbstractText NlmCategory="UNASSIGNED">In this paper, we present an extended data-driven haptic rendering method capable of reproducing force responses during pushing and sliding interaction on a large surface area. The main part of the approach is a novel input variable set for the training of an interpolation model, which incorporates the position of a proxy - an imaginary contact point on the undeformed surface. This allows us to estimate friction in both sliding and sticking states in a unified framework. Estimating the proxy position is done in real-time based on simulation using a sliding yield surface - a surface defining a border between the sliding and sticking regions in the external force space. During modeling, the sliding yield surface is first identified via an automated palpation procedure. Then, through manual palpation on a target surface, input data and resultant force data are acquired. The data are used to build a radial basis interpolation model. During rendering, this input-output mapping interpolation model is used to estimate force responses in real-time in accordance with the interaction input. Physical performance evaluation demonstrates that our approach achieves reasonably high estimation accuracy. A user study also shows plausible perceptual realism under diverse and extensive exploration.</AbstractText></Abstract><AuthorList><Author><LastName>Yim</LastName><ForeName>Sunghoon</ForeName><Initials>S</Initials></Author><Author><LastName>Jeon</LastName><ForeName>Seokhee</ForeName><Initials>S</Initials></Author><Author><LastName>Choi</LastName><ForeName>Seungmoon</ForeName><Initials>S</Initials></Author></AuthorList><Language>ENG</Language><PublicationTypeList><PublicationType UI="">JOURNAL ARTICLE</PublicationType></PublicationTypeList><ArticleDate DateType="Electronic"><Year>2016</Year><Month>5</Month><Day>23</Day></ArticleDate></Article><MedlineJournalInfo><MedlineTA>IEEE Trans Haptics</MedlineTA><NlmUniqueID>101491191</NlmUniqueID><ISSNLinking>1939-1412</ISSNLinking></MedlineJournalInfo></MedlineCitation><PubmedData><History><PubMedPubDate PubStatus="entrez"><Year>2016</Year><Month>6</Month><Day>1</Day><Hour>6</Hour><Minute>0</Minute></PubMedPubDate><PubMedPubDate PubStatus="pubmed"><Year>2016</Year><Month>6</Month><Day>1</Day><Hour>6</Hour><Minute>0</Minute></PubMedPubDate><PubMedPubDate PubStatus="medline"><Year>2016</Year><Month>6</Month><Day>1</Day><Hour>6</Hour><Minute>0</Minute></PubMedPubDate></History><PublicationStatus>aheadofprint</PublicationStatus><ArticleIdList><ArticleId IdType="doi">10.1109/TOH.2016.2571690</ArticleId><ArticleId IdType="pubmed">27244750</ArticleId></ArticleIdList></PubmedData></pubmed><affiliations><list></list><tree><noCountry><name sortKey="Choi, Seungmoon" sort="Choi, Seungmoon" uniqKey="Choi S" first="Seungmoon" last="Choi">Seungmoon Choi</name><name sortKey="Jeon, Seokhee" sort="Jeon, Seokhee" uniqKey="Jeon S" first="Seokhee" last="Jeon">Seokhee Jeon</name><name sortKey="Yim, Sunghoon" sort="Yim, Sunghoon" uniqKey="Yim S" first="Sunghoon" last="Yim">Sunghoon Yim</name></noCountry></tree></affiliations></record>Pour manipuler ce document sous Unix (Dilib)
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