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- Publisher Website: 10.1109/TRO.2016.2632160
- Scopus: eid_2-s2.0-85007348391
- WOS: WOS:000399348900008
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Article: Parallel Motion Planning Using Poisson-Disk Sampling
Title | Parallel Motion Planning Using Poisson-Disk Sampling |
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Authors | |
Keywords | Motion planning parallel algorithm Poisson-disk sampling |
Issue Date | 2017 |
Citation | IEEE Transactions on Robotics, 2017, v. 33, n. 2, p. 359-371 How to Cite? |
Abstract | We present a rapidly exploring-random-Tree-based parallel motion planning algorithm that uses the maximal Poisson-disk sampling scheme. Our approach exploits the free-disk property of the maximal Poisson-disk samples to generate nodes and perform tree expansion. Furthermore, we use an adaptive scheme to generate more samples in challenging regions of the configuration space. The Poisson-disk sampling results in improved parallel performance and we highlight the performance benefits on multicore central processing units as well as manycore graphics processing units on different benchmarks. |
Persistent Identifier | http://hdl.handle.net/10722/308712 |
ISSN | 2021 Impact Factor: 6.835 2020 SCImago Journal Rankings: 2.027 |
ISI Accession Number ID |
DC Field | Value | Language |
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dc.contributor.author | Park, Chonhyon | - |
dc.contributor.author | Pan, Jia | - |
dc.contributor.author | Manocha, Dinesh | - |
dc.date.accessioned | 2021-12-08T07:49:58Z | - |
dc.date.available | 2021-12-08T07:49:58Z | - |
dc.date.issued | 2017 | - |
dc.identifier.citation | IEEE Transactions on Robotics, 2017, v. 33, n. 2, p. 359-371 | - |
dc.identifier.issn | 1552-3098 | - |
dc.identifier.uri | http://hdl.handle.net/10722/308712 | - |
dc.description.abstract | We present a rapidly exploring-random-Tree-based parallel motion planning algorithm that uses the maximal Poisson-disk sampling scheme. Our approach exploits the free-disk property of the maximal Poisson-disk samples to generate nodes and perform tree expansion. Furthermore, we use an adaptive scheme to generate more samples in challenging regions of the configuration space. The Poisson-disk sampling results in improved parallel performance and we highlight the performance benefits on multicore central processing units as well as manycore graphics processing units on different benchmarks. | - |
dc.language | eng | - |
dc.relation.ispartof | IEEE Transactions on Robotics | - |
dc.subject | Motion planning | - |
dc.subject | parallel algorithm | - |
dc.subject | Poisson-disk sampling | - |
dc.title | Parallel Motion Planning Using Poisson-Disk Sampling | - |
dc.type | Article | - |
dc.description.nature | link_to_subscribed_fulltext | - |
dc.identifier.doi | 10.1109/TRO.2016.2632160 | - |
dc.identifier.scopus | eid_2-s2.0-85007348391 | - |
dc.identifier.volume | 33 | - |
dc.identifier.issue | 2 | - |
dc.identifier.spage | 359 | - |
dc.identifier.epage | 371 | - |
dc.identifier.isi | WOS:000399348900008 | - |