MIT Libraries logoDSpace@MIT

MIT
View Item 
  • DSpace@MIT Home
  • MIT Open Access Articles
  • MIT Open Access Articles
  • View Item
  • DSpace@MIT Home
  • MIT Open Access Articles
  • MIT Open Access Articles
  • View Item
JavaScript is disabled for your browser. Some features of this site may not work without it.

Massively parallelizing the RRT and the RRT*

Author(s)
Karaman, Sertac; Frazzoli, Emilio; Bialkowski, Joshua John
Thumbnail
DownloadFrazzoli_Massively parallelizing.pdf (480.4Kb)
OPEN_ACCESS_POLICY

Open Access Policy

Creative Commons Attribution-Noncommercial-Share Alike

Terms of use
Creative Commons Attribution-Noncommercial-Share Alike 3.0 http://creativecommons.org/licenses/by-nc-sa/3.0/
Metadata
Show full item record
Abstract
In 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.
Date issued
2011-09
URI
http://hdl.handle.net/1721.1/81448
Department
Massachusetts Institute of Technology. Department of Aeronautics and Astronautics; Massachusetts Institute of Technology. Department of Electrical Engineering and Computer Science
Journal
Proceedings of the 2011 IEEE/RSJ International Conference on Intelligent Robots and Systems
Publisher
Institute of Electrical and Electronics Engineers (IEEE)
Citation
Bialkowski, 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.
Version: Author's final manuscript
ISBN
978-1-61284-456-5
978-1-61284-454-1
978-1-61284-455-8

Collections
  • MIT Open Access Articles

Browse

All of DSpaceCommunities & CollectionsBy Issue DateAuthorsTitlesSubjectsThis CollectionBy Issue DateAuthorsTitlesSubjects

My Account

Login

Statistics

OA StatisticsStatistics by CountryStatistics by Department
MIT Libraries
PrivacyPermissionsAccessibilityContact us
MIT
Content created by the MIT Libraries, CC BY-NC unless otherwise noted. Notify us about copyright concerns.