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Parallel computation of configuration space

Published online by Cambridge University Press:  09 March 2009

J. Solano González  and
D.I. Jonest
J. Solano González
Affiliation:
Instituto de Investigaciones en Matematicas y en Sistemas, Departamento de Electronica y Automatizacion, Universidad Nacional Autonoma de Mexico, Apartado Postal 20–276, Admon - No 20, 01000, Mexico, DF (Mexico)
D.I. Jonest
Affiliation:
School of Electronic Engineering and Computer Systems, University of Wales, Dean Street, Bangor, Gwynedd LL57IUT, North Wales (UK).
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Summary

Many motion planning methods use Configuration Space to represent a robot manipulator's range of motion and the obstacles which exist in its environment. The Cartesian to Configuration Space mapping is computationally intensive and this paper describes how the execution time can be decreased by using parallel processing. The natural tree structure of the algorithm is exploited to partition the computation into parallel tasks. An implementation programmed in the occam2 parallel computer language running on a network of INMOS transputers is described. The benefits of dynamically scheduling the tasks onto the processors are explained and verified by means of measured execution times on various processor network topologies. It is concluded that excellent speed-up and efficiency can be achieved provided that proper account is taken of the variable task lengths in the computation.

Keywords

Configuration spaceParallel computationObstaclesMotion planning

Information

Type
Article
Information
Robotica , Volume 14 , Issue 2 , March 1996 , pp. 205 - 212
Copyright
Copyright © Cambridge University Press 1996

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