Identification and Active Exploration of Deformable Object Boundary Constraints through Robotic Manipulation
Identifieur interne : 003692 ( Ncbi/Checkpoint ); précédent : 003691; suivant : 003693Identification and Active Exploration of Deformable Object Boundary Constraints through Robotic Manipulation
Auteurs : Pasu Boonvisut [États-Unis] ; M. Cenk Cavusoglu [États-Unis]Source :
- The International journal of robotics research [ 0278-3649 ] ; 2014.
Abstract
Robotic motion planning algorithms for manipulation of deformable objects, such as in medical robotics applications, rely on accurate estimations of object deformations that occur during manipulation. An estimation of the tissue response (for off-line planning or real-time on-line re-planning), in turn, requires knowledge of both object constitutive parameters and boundary constraints. In this paper, a novel algorithm for estimating boundary constraints of deformable objects from robotic manipulation data is presented. The proposed algorithm uses tissue deformation data collected with a vision system, and employs a multi-stage hill climbing procedure to estimate the boundary constraints of the object. An active exploration technique, which uses an information maximization approach, is also proposed to extend the identification algorithm. The effects of uncertainties on the proposed methods are analyzed in simulation. The results of experimental evaluation of the methods are also presented.
Url:
DOI: 10.1177/0278364914536939
PubMed: 25684836
PubMed Central: 4324691
Affiliations:
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Cenk Cavusoglu</name><affiliation wicri:level="2"><nlm:aff id="A1">Electrical Engineering and Computer Science Department, Case Western Reserve University, Cleveland, OH, USA</nlm:aff><country xml:lang="fr">États-Unis</country><wicri:regionArea>Electrical Engineering and Computer Science Department, Case Western Reserve University, Cleveland, OH</wicri:regionArea><placeName><region type="state">Ohio</region></placeName></affiliation></author></titleStmt><publicationStmt><idno type="wicri:source">PMC</idno><idno type="pmid">25684836</idno><idno type="pmc">4324691</idno><idno type="url">http://www.ncbi.nlm.nih.gov/pmc/articles/PMC4324691</idno><idno type="RBID">PMC:4324691</idno><idno type="doi">10.1177/0278364914536939</idno><date when="2014">2014</date><idno type="wicri:Area/Pmc/Corpus">001816</idno><idno type="wicri:Area/Pmc/Curation">001816</idno><idno type="wicri:Area/Pmc/Checkpoint">000B89</idno><idno type="wicri:Area/Ncbi/Merge">003692</idno><idno type="wicri:Area/Ncbi/Curation">003692</idno><idno type="wicri:Area/Ncbi/Checkpoint">003692</idno></publicationStmt><sourceDesc><biblStruct><analytic><title xml:lang="en" level="a" type="main">Identification and Active Exploration of Deformable Object Boundary Constraints through Robotic Manipulation</title><author><name sortKey="Boonvisut, Pasu" sort="Boonvisut, Pasu" uniqKey="Boonvisut P" first="Pasu" last="Boonvisut">Pasu Boonvisut</name><affiliation wicri:level="2"><nlm:aff id="A1">Electrical Engineering and Computer Science Department, Case Western Reserve University, Cleveland, OH, USA</nlm:aff><country xml:lang="fr">États-Unis</country><wicri:regionArea>Electrical Engineering and Computer Science Department, Case Western Reserve University, Cleveland, OH</wicri:regionArea><placeName><region type="state">Ohio</region></placeName></affiliation></author><author><name sortKey="Cavusoglu, M Cenk" sort="Cavusoglu, M Cenk" uniqKey="Cavusoglu M" first="M. Cenk" last="Cavusoglu">M. Cenk Cavusoglu</name><affiliation wicri:level="2"><nlm:aff id="A1">Electrical Engineering and Computer Science Department, Case Western Reserve University, Cleveland, OH, USA</nlm:aff><country xml:lang="fr">États-Unis</country><wicri:regionArea>Electrical Engineering and Computer Science Department, Case Western Reserve University, Cleveland, OH</wicri:regionArea><placeName><region type="state">Ohio</region></placeName></affiliation></author></analytic><series><title level="j">The International journal of robotics research</title><idno type="ISSN">0278-3649</idno><idno type="eISSN">1741-3176</idno><imprint><date when="2014">2014</date></imprint></series></biblStruct></sourceDesc></fileDesc><profileDesc><textClass></textClass></profileDesc></teiHeader><front><div type="abstract" xml:lang="en"><p id="P1">Robotic motion planning algorithms for manipulation of deformable objects, such as in medical robotics applications, rely on accurate estimations of object deformations that occur during manipulation. An estimation of the tissue response (for off-line planning or real-time on-line re-planning), in turn, requires knowledge of both object constitutive parameters and boundary constraints. In this paper, a novel algorithm for estimating boundary constraints of deformable objects from robotic manipulation data is presented. The proposed algorithm uses tissue deformation data collected with a vision system, and employs a multi-stage hill climbing procedure to estimate the boundary constraints of the object. An active exploration technique, which uses an information maximization approach, is also proposed to extend the identification algorithm. The effects of uncertainties on the proposed methods are analyzed in simulation. 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