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dc.contributor.authorKaraman, Sertac
dc.contributor.authorFrazzoli, Emilio
dc.contributor.authorBialkowski, Joshua John
dc.date.accessioned2013-10-21T14:44:56Z
dc.date.available2013-10-21T14:44:56Z
dc.date.issued2011-09
dc.identifier.isbn978-1-61284-456-5
dc.identifier.isbn978-1-61284-454-1
dc.identifier.isbn978-1-61284-455-8
dc.identifier.urihttp://hdl.handle.net/1721.1/81448
dc.description.abstractIn recent years, the growth of the computational power available in the Central Processing Units (CPUs) of consumer computers has tapered significantly. At the same time, growth in the computational power available in the Graphics Processing Units (GPUs) has remained strong. Algorithms that can be implemented on GPUs today are not only limited to graphics processing, but include scientific computation and beyond. This paper is concerned with massively parallel implementations of incremental sampling-based robot motion planning algorithms, namely the widely-used Rapidly-exploring Random Tree (RRT) algorithm and its asymptotically-optimal counterpart called RRT*. We demonstrate an example implementation of RRT and RRT* motion-planning algorithm for a high-dimensional robotic manipulator that takes advantage of an NVidia CUDA-enabled GPU. We focus on parallelizing the collision-checking procedure, which is generally recognized as the computationally expensive component of sampling-based motion planning algorithms. Our experimental results indicate significant speedup when compared to CPU implementations, leading to practical algorithms for optimal motion planning in high-dimensional configuration spaces.en_US
dc.language.isoen_US
dc.publisherInstitute of Electrical and Electronics Engineers (IEEE)en_US
dc.relation.isversionofhttp://dx.doi.org/10.1109/IROS.2011.6095053en_US
dc.rightsCreative Commons Attribution-Noncommercial-Share Alike 3.0en_US
dc.rights.urihttp://creativecommons.org/licenses/by-nc-sa/3.0/en_US
dc.sourceMIT web domainen_US
dc.titleMassively parallelizing the RRT and the RRT*en_US
dc.typeArticleen_US
dc.identifier.citationBialkowski, Joshua, Sertac Karaman, and Emilio Frazzoli. “Massively parallelizing the RRT and the RRT.” In 2011 IEEE/RSJ International Conference on Intelligent Robots and Systems, 3513-3518. Institute of Electrical and Electronics Engineers, 2011.en_US
dc.contributor.departmentMassachusetts Institute of Technology. Department of Aeronautics and Astronauticsen_US
dc.contributor.departmentMassachusetts Institute of Technology. Department of Electrical Engineering and Computer Scienceen_US
dc.contributor.mitauthorBialkowski, Joshua Johnen_US
dc.contributor.mitauthorKaraman, Sertacen_US
dc.contributor.mitauthorFrazzoli, Emilioen_US
dc.relation.journalProceedings of the 2011 IEEE/RSJ International Conference on Intelligent Robots and Systemsen_US
dc.eprint.versionAuthor's final manuscripten_US
dc.type.urihttp://purl.org/eprint/type/ConferencePaperen_US
eprint.statushttp://purl.org/eprint/status/NonPeerRevieweden_US
dspace.orderedauthorsBialkowski, Joshua; Karaman, Sertac; Frazzoli, Emilioen_US
dc.identifier.orcidhttps://orcid.org/0000-0002-0505-1400
dc.identifier.orcidhttps://orcid.org/0000-0002-2225-7275
mit.licenseOPEN_ACCESS_POLICYen_US
mit.metadata.statusComplete


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