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- Publisher Website: 10.1109/LRA.2015.2502919
- Scopus: eid_2-s2.0-85058585358
- WOS: WOS:000413719900003
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Article: Efficient Penetration Depth Computation Between Rigid Models Using Contact Space Propagation Sampling
Title | Efficient Penetration Depth Computation Between Rigid Models Using Contact Space Propagation Sampling |
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Authors | |
Keywords | Contact Modelling Simulation and Animation |
Issue Date | 2016 |
Citation | IEEE Robotics and Automation Letters, 2016, v. 1, n. 1, p. 10-17 How to Cite? |
Abstract | We 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. |
Persistent Identifier | http://hdl.handle.net/10722/308896 |
ISI Accession Number ID |
DC Field | Value | Language |
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dc.contributor.author | He, Liang | - |
dc.contributor.author | Pan, Jia | - |
dc.contributor.author | Li, Danwei | - |
dc.contributor.author | Manocha, Dinesh | - |
dc.date.accessioned | 2021-12-08T07:50:21Z | - |
dc.date.available | 2021-12-08T07:50:21Z | - |
dc.date.issued | 2016 | - |
dc.identifier.citation | IEEE Robotics and Automation Letters, 2016, v. 1, n. 1, p. 10-17 | - |
dc.identifier.uri | http://hdl.handle.net/10722/308896 | - |
dc.description.abstract | We 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. | - |
dc.language | eng | - |
dc.relation.ispartof | IEEE Robotics and Automation Letters | - |
dc.subject | Contact Modelling | - |
dc.subject | Simulation and Animation | - |
dc.title | Efficient Penetration Depth Computation Between Rigid Models Using Contact Space Propagation Sampling | - |
dc.type | Article | - |
dc.description.nature | link_to_subscribed_fulltext | - |
dc.identifier.doi | 10.1109/LRA.2015.2502919 | - |
dc.identifier.scopus | eid_2-s2.0-85058585358 | - |
dc.identifier.volume | 1 | - |
dc.identifier.issue | 1 | - |
dc.identifier.spage | 10 | - |
dc.identifier.epage | 17 | - |
dc.identifier.eissn | 2377-3766 | - |
dc.identifier.isi | WOS:000413719900003 | - |