Handle URI:
http://hdl.handle.net/10754/599875
Title:
The anatomy of a distributed motion planning roadmap
Authors:
Jacobs, Sam Ade; Amato, Nancy M.
Abstract:
© 2014 IEEE. In this paper, we evaluate and compare the quality and structure of roadmaps constructed from parallelizing sampling-based motion planning algorithms against that of roadmaps constructed using sequential planner. Also, we make an argument and provide experimental results that show that motion planning problems involving heterogenous environments (common in most realistic and large-scale motion planning) is a natural fit for spatial subdivision-based parallel processing. Spatial subdivision-based parallel processing approach is suited for heterogeneous environments because it allows for local adaption in solving a global problem while taking advantage of scalability that is possible with parallel processing.
Citation:
Jacobs SA, Amato NM (2014) The anatomy of a distributed motion planning roadmap. 2014 IEEE/RSJ International Conference on Intelligent Robots and Systems. Available: http://dx.doi.org/10.1109/IROS.2014.6942979.
Publisher:
Institute of Electrical and Electronics Engineers (IEEE)
Journal:
2014 IEEE/RSJ International Conference on Intelligent Robots and Systems
KAUST Grant Number:
KUS-C1-016-04
Issue Date:
Sep-2014
DOI:
10.1109/IROS.2014.6942979
Type:
Conference Paper
Sponsors:
This research supported in part by NSF awards CNS-0551685, CCF-0833199, CCF-0830753, IIS-0917266, IIS-0916053, EFRI-1240483, RI-1217991, by NSF/DNDO award 2008-DN-077-ARI018-02, by NIH NCIR25 CA090301-11, by DOE awards DE-FC52-08NA28616, DE-AC02-06CH11357, B575363, B575366, by THECB NHARP award 000512-0097-2009, by Samsung, Chevron, IBM, Intel, Oracle/Sun and by Award KUS-C1-016-04, made by King Abdullah University of Science and Technology(KAUST). This research used resources of the National Energy ResearchScientific Computing Center, which is supported by the Office of Science ofthe U.S. Department of Energy under Contract No. DE-AC02-05CH11231.
Appears in Collections:
Publications Acknowledging KAUST Support

Full metadata record

DC FieldValue Language
dc.contributor.authorJacobs, Sam Adeen
dc.contributor.authorAmato, Nancy M.en
dc.date.accessioned2016-02-28T06:31:27Zen
dc.date.available2016-02-28T06:31:27Zen
dc.date.issued2014-09en
dc.identifier.citationJacobs SA, Amato NM (2014) The anatomy of a distributed motion planning roadmap. 2014 IEEE/RSJ International Conference on Intelligent Robots and Systems. Available: http://dx.doi.org/10.1109/IROS.2014.6942979.en
dc.identifier.doi10.1109/IROS.2014.6942979en
dc.identifier.urihttp://hdl.handle.net/10754/599875en
dc.description.abstract© 2014 IEEE. In this paper, we evaluate and compare the quality and structure of roadmaps constructed from parallelizing sampling-based motion planning algorithms against that of roadmaps constructed using sequential planner. Also, we make an argument and provide experimental results that show that motion planning problems involving heterogenous environments (common in most realistic and large-scale motion planning) is a natural fit for spatial subdivision-based parallel processing. Spatial subdivision-based parallel processing approach is suited for heterogeneous environments because it allows for local adaption in solving a global problem while taking advantage of scalability that is possible with parallel processing.en
dc.description.sponsorshipThis research supported in part by NSF awards CNS-0551685, CCF-0833199, CCF-0830753, IIS-0917266, IIS-0916053, EFRI-1240483, RI-1217991, by NSF/DNDO award 2008-DN-077-ARI018-02, by NIH NCIR25 CA090301-11, by DOE awards DE-FC52-08NA28616, DE-AC02-06CH11357, B575363, B575366, by THECB NHARP award 000512-0097-2009, by Samsung, Chevron, IBM, Intel, Oracle/Sun and by Award KUS-C1-016-04, made by King Abdullah University of Science and Technology(KAUST). This research used resources of the National Energy ResearchScientific Computing Center, which is supported by the Office of Science ofthe U.S. Department of Energy under Contract No. DE-AC02-05CH11231.en
dc.publisherInstitute of Electrical and Electronics Engineers (IEEE)en
dc.titleThe anatomy of a distributed motion planning roadmapen
dc.typeConference Paperen
dc.identifier.journal2014 IEEE/RSJ International Conference on Intelligent Robots and Systemsen
dc.contributor.institutionABB USA, Norwalk, United Statesen
dc.contributor.institutionTexas A and M University, College Station, United Statesen
kaust.grant.numberKUS-C1-016-04en
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