Abstract
This article is concerned with generation of kinematic trajectories for manipulators. For quick planning we use a graph-based algorithm that already allows to plan at least some motions from the beginning of the graph construction process, and hence omits long preprocessing phases. Unless specific tasks are given, we use random configurations for incremental graph construction. The graph is constructed in configuration-space of manipulators. Its nodes serve as subgoals and its edges as collision free sub-trajectories for planning new, unknown trajectories. We show the high performance of this approach with respect to preprocessing and trajectory generation time, as well as planning success in a realistic simulation of a real world manipulator task.
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