Hierarchical Topometric Representation of 3D Robotic Maps
This is an incremental improvement for robotics navigation, enabling more flexible map representations.
The paper tackles the problem of generating hierarchical, volumetric topological maps from 3D point clouds for robotics, resulting in a method that handles multi-storey structures and sloping roofs while producing outputs with metric information suitable for various applications.
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.