  In this paper, we propose a method for generating a hierarchical, volumetric
topological map from 3D point clouds. There are three basic hierarchical levels
in our map: $storey - region - volume$. The advantages of our method are
reflected in both input and output. In terms of input, we accept multi-storey
point clouds and building structures with sloping roofs or ceilings. In terms
of output, we can generate results with metric information of different
dimensionality, that are suitable for different robotics applications. The
algorithm generates the volumetric representation by generating $volumes$ from
a 3D voxel occupancy map. We then add $passage$s (connections between
$volumes$), combine small $volumes$ into a big $region$ and use a 2D
segmentation method for better topological representation. We evaluate our
method on several freely available datasets. The experiments highlight the
advantages of our approach.
