Randomized parallel motion planning for robot manipulators

We present a novel approach to parallel motion planning for
robot manipulators in 3D workspaces. The approach is based on a
randomized 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 configuration 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 configuration to the goal via a number of
randomly generated subgoal configurations. 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 out on the parallel 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 efficiency of motion planning significantly.
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