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Parallel approaches for singular value decomposition as applied to robotic manipulator Jacobians

Date

2002

Authors

Siegel, Howard Jay, author
Maciejewski, Anthony A., author
Ulrey, Renard, author
Braun, Tracy D., author
Plenum Publishing Corporation, publisher

Journal Title

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Volume Title

Abstract

The system of equations that govern kinematically redundant robotic manipulators is commonly solved by finding the singular value decomposition (SVD) of the corresponding Jacobian matrix. This can require a considerable amount of time to compute, thus a parallel SVD algorithm reducing execution time is sought. The approach employed here lends itself to parallelization by using Givens rotations and information from previous decompositions. The key contribution of this research is the presentation and implementation of parallel SVD algorithms to compute the SVD for a set of Jacobians that represent various different joint failure scenarios. Results from implementation of the algorithm on a MasPar MP-1, an IBM SP2, and the PASM prototype parallel computers are compared. Specific issues considered for each implementation include: how data is mapped to the processing elements, the effect that increasing the number of processing elements has on execution time, the type of parallel architecture used, and trade-offs between modes of parallelism.

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Subject

MasPar MP-1
redundant manipulator
IBM SP2
robotic-control
singular value decomposition

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