  A simple sample-based planning method is presented which approximates
connected regions of free space with volumes in Configuration space instead of
points. The algorithm produces very sparse trees compared to point-based
planning approaches, yet it maintains probabilistic completeness guarantees.
The planner is shown to improve performance on a variety of planning problems,
by focusing sampling on more challenging regions of a planning problem,
including collision boundary areas such as narrow passages.
