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Randomized Parallel Motion Planning for Robot Manipulators
Caigong Qin , Dominik Henrich

Abstract (english)
We have presented a novel approach to parallel motion planning for robot manipulators in 3D workspaces. The approach is based on arandomized parallel search algorithm and focuses on solving the path planning problem for industrial robot arms working in a reasonably cluttered workspace. The path planning system works in the discretized con guration space, which needs not to be represented explicitly. The parallel search is conducted by a number of rule-based sequential search processes, which work to find a path connecting the initial con guration to the goal via a number of randomly generated subgoal con gurations. Since the planning performs only on-line collision tests with proper proximity information without using pre-computed information, the approach is suitable for planning problems with multirobot or dynamic environments. The implementation has been carried outontheparallel virtual machine (PVM) of a cluster of SUN4 workstations and SGI machines. The experimental results have shown that the approach works well for a 6-dof robot arm in a reasonably cluttered environment, and that parallel computation increases the e ciency of motion planning signi cantly.

Publication data

Year: 1996
Publication date: 01. May 1996
Source: Technical Report 5/96, Computer Science Department, University of Karlsruhe, 1996
Project: SKALP , PARO
Referrer: http://www.ai3.uni-bayreuth.de/resypub/?mode=pub_show&pub_ref=qin1996a

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no_series_249.djvu   250.6K   english   DJVU   download preprint
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