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 passages (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.

在本文中，我们提出了一种从 3D 点云生成分层体积拓扑图的方法。在我们的地图中有三个基本层级：\(storey - region - volume\)。我们方法的优势体现在输入和输出上。在输入方面，我们接受多层点云和带有倾斜屋顶或天花板的建筑结构。在输出方面，我们可以生成具有不同维度的度量信息的结果，适用于不同的机器人应用。该算法通过从 3D 体素占用图生成体积来生成体积表示。然后我们添加通道s（卷之间的连接），结合小卷进入一个大区域并使用二维分割方法以获得更好的拓扑表示。我们在几个免费可用的数据集上评估我们的方法。实验突出了我们方法的优点。