  Robotic planning systems model spatial relations in detail as these are
needed for manipulation tasks. In contrast to this, other physical attributes
of objects and the effect of devices are usually oversimplified and expressed
by abstract compound attributes. This limits the ability of planners to find
alternative solutions. We propose to break these compound attributes down into
a shared set of elementary attributes. This strongly facilitates generalization
between different tasks and environments and thus helps to find innovative
solutions. On the down-side, this generalization comes with an increased
complexity of the solution space. Therefore, as the main contribution of the
paper, we propose a method that splits the planning problem into a sequence of
views, where in each view only an increasing subset of attributes is
considered. We show that this view-based strategy offers a good compromise
between planning speed and quality of the found plan, and discuss its general
applicability and limitations.
