Parallelizing RRT on large-scale distributed-memory architectures

Didier Devaurs; Thierry Siméon; Juan Cortés

doi:10.1109/TRO.2013.2239571

Parallelizing RRT on large-scale distributed-memory architectures

Didier Devaurs^*, Thierry Siméon, Juan Cortés

^*Corresponding author for this work

Computer And Information Sciences

Research output: Contribution to journal › Article › peer-review

29 Citations (Scopus)

Abstract

This paper addresses the problem of parallelizing the Rapidly-exploring Random Tree (RRT) algorithm on large-scale distributed-memory architectures, using the message passing interface. We compare three parallel versions of RRT based on classical parallelization schemes. We evaluate them on different motion-planning problems and analyze the various factors influencing their performance.

Original language	English
Pages (from-to)	571-579
Number of pages	9
Journal	IEEE Transactions on Robotics
Volume	29
Issue number	2
Early online date	29 Jan 2013
DOIs	https://doi.org/10.1109/TRO.2013.2239571
Publication status	Published - 1 Apr 2013

Keywords

distributed memory
message passing
parallel algorithms
path planning
rapidly-exploring random tree (RRT)

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10.1109/TRO.2013.2239571

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title = "Parallelizing RRT on large-scale distributed-memory architectures",

abstract = "This paper addresses the problem of parallelizing the Rapidly-exploring Random Tree (RRT) algorithm on large-scale distributed-memory architectures, using the message passing interface. We compare three parallel versions of RRT based on classical parallelization schemes. We evaluate them on different motion-planning problems and analyze the various factors influencing their performance.",

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AB - This paper addresses the problem of parallelizing the Rapidly-exploring Random Tree (RRT) algorithm on large-scale distributed-memory architectures, using the message passing interface. We compare three parallel versions of RRT based on classical parallelization schemes. We evaluate them on different motion-planning problems and analyze the various factors influencing their performance.

KW - distributed memory

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KW - parallel algorithms

KW - path planning

KW - rapidly-exploring random tree (RRT)

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Parallelizing RRT on large-scale distributed-memory architectures

Abstract

Keywords

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