Please use this identifier to cite or link to this item: http://localhost/handle/Hannan/659527
Full metadata record
DC FieldValueLanguage
dc.contributor.authorLiang Heen_US
dc.contributor.authorJia Panen_US
dc.contributor.authorDanwei Lien_US
dc.contributor.authorDinesh Manochaen_US
dc.date.accessioned2020-05-20T10:37:26Z-
dc.date.available2020-05-20T10:37:26Z-
dc.date.issued2016en_US
dc.identifier.issn2377-3766en_US
dc.identifier.other10.1109/LRA.2015.2502919en_US
dc.identifier.urihttp://localhost/handle/Hannan/170547en_US
dc.identifier.urihttp://localhost/handle/Hannan/659527-
dc.descriptionen_US
dc.description.abstractWe present a novel method to compute the approximate global penetration depth (PD) between two nonconvex geometric models. Our approach consists of two phases: offline precomputation and run-time queries. In the first phase, our formulation uses a novel sampling algorithm to precompute an approximation of the high-dimensional contact space between the pair of models. As compared with prior random sampling algorithms for contact space approximation, our propagation sampling considerably speeds up the precomputation and yields a high quality approximation. At run-time, we perform a nearest-neighbor query and local projection to efficiently compute the translational or generalized PD. We demonstrate the performance of our approach on complex 3-D benchmarks with tens or hundreds or thousands of triangles, and we observe significant improvement over previous methods in terms of accuracy, with a modest improvement in the run-time performance.en_US
dc.publisherIEEEen_US
dc.relation.haspart7342933.pdfen_US
dc.subjectContact Modelling|Simulation and Animationen_US
dc.titleEfficient Penetration Depth Computation Between Rigid Models Using Contact Space Propagation Samplingen_US
dc.typeArticleen_US
dc.journal.volume1en_US
dc.journal.issue1en_US
dc.journal.titleIEEE Robotics and Automation Lettersen_US
Appears in Collections:2016

Files in This Item:
File Description SizeFormat 
7342933.pdf721.03 kBAdobe PDFThumbnail
Preview File
Full metadata record
DC FieldValueLanguage
dc.contributor.authorLiang Heen_US
dc.contributor.authorJia Panen_US
dc.contributor.authorDanwei Lien_US
dc.contributor.authorDinesh Manochaen_US
dc.date.accessioned2020-05-20T10:37:26Z-
dc.date.available2020-05-20T10:37:26Z-
dc.date.issued2016en_US
dc.identifier.issn2377-3766en_US
dc.identifier.other10.1109/LRA.2015.2502919en_US
dc.identifier.urihttp://localhost/handle/Hannan/170547en_US
dc.identifier.urihttp://localhost/handle/Hannan/659527-
dc.descriptionen_US
dc.description.abstractWe present a novel method to compute the approximate global penetration depth (PD) between two nonconvex geometric models. Our approach consists of two phases: offline precomputation and run-time queries. In the first phase, our formulation uses a novel sampling algorithm to precompute an approximation of the high-dimensional contact space between the pair of models. As compared with prior random sampling algorithms for contact space approximation, our propagation sampling considerably speeds up the precomputation and yields a high quality approximation. At run-time, we perform a nearest-neighbor query and local projection to efficiently compute the translational or generalized PD. We demonstrate the performance of our approach on complex 3-D benchmarks with tens or hundreds or thousands of triangles, and we observe significant improvement over previous methods in terms of accuracy, with a modest improvement in the run-time performance.en_US
dc.publisherIEEEen_US
dc.relation.haspart7342933.pdfen_US
dc.subjectContact Modelling|Simulation and Animationen_US
dc.titleEfficient Penetration Depth Computation Between Rigid Models Using Contact Space Propagation Samplingen_US
dc.typeArticleen_US
dc.journal.volume1en_US
dc.journal.issue1en_US
dc.journal.titleIEEE Robotics and Automation Lettersen_US
Appears in Collections:2016

Files in This Item:
File Description SizeFormat 
7342933.pdf721.03 kBAdobe PDFThumbnail
Preview File
Full metadata record
DC FieldValueLanguage
dc.contributor.authorLiang Heen_US
dc.contributor.authorJia Panen_US
dc.contributor.authorDanwei Lien_US
dc.contributor.authorDinesh Manochaen_US
dc.date.accessioned2020-05-20T10:37:26Z-
dc.date.available2020-05-20T10:37:26Z-
dc.date.issued2016en_US
dc.identifier.issn2377-3766en_US
dc.identifier.other10.1109/LRA.2015.2502919en_US
dc.identifier.urihttp://localhost/handle/Hannan/170547en_US
dc.identifier.urihttp://localhost/handle/Hannan/659527-
dc.descriptionen_US
dc.description.abstractWe present a novel method to compute the approximate global penetration depth (PD) between two nonconvex geometric models. Our approach consists of two phases: offline precomputation and run-time queries. In the first phase, our formulation uses a novel sampling algorithm to precompute an approximation of the high-dimensional contact space between the pair of models. As compared with prior random sampling algorithms for contact space approximation, our propagation sampling considerably speeds up the precomputation and yields a high quality approximation. At run-time, we perform a nearest-neighbor query and local projection to efficiently compute the translational or generalized PD. We demonstrate the performance of our approach on complex 3-D benchmarks with tens or hundreds or thousands of triangles, and we observe significant improvement over previous methods in terms of accuracy, with a modest improvement in the run-time performance.en_US
dc.publisherIEEEen_US
dc.relation.haspart7342933.pdfen_US
dc.subjectContact Modelling|Simulation and Animationen_US
dc.titleEfficient Penetration Depth Computation Between Rigid Models Using Contact Space Propagation Samplingen_US
dc.typeArticleen_US
dc.journal.volume1en_US
dc.journal.issue1en_US
dc.journal.titleIEEE Robotics and Automation Lettersen_US
Appears in Collections:2016

Files in This Item:
File Description SizeFormat 
7342933.pdf721.03 kBAdobe PDFThumbnail
Preview File