[show abstract]
[hide abstract]
ABSTRACT: Probabilistic roadmap planning methods have been shown to perform
well in a number of practical situations, but their performance degrades
when paths are required to pass through narrow passages in the free
space. We propose a new method of sampling the configuration space in
which randomly generated configurations, free or not, are retracted onto
the medial axis of the free space. We give algorithms that perform this
retraction while avoiding explicit computation of the medial axis, and
we show that sampling and retracting in this manner increases the number
of nodes found in small volume corridors in a way that is independent of
the volume of the corridor and depends only on the characteristics of
the obstacles bounding it. Theoretical and experimental results are
given to show that this improves performance on problems requiring
traversal of narrow passages
Robotics and Automation, 1999. Proceedings. 1999 IEEE International Conference on; 02/1999
