Voronoi Random Fields: Extracting Topological Structure of Indoor Environments via Place Labeling
Voronoi Random Fields: Extracting Topological Structure of Indoor Environments via Place Labeling
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发表时间：
2007-01
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通讯作者：
Stephen Friedman;H. Pasula;D. Fox
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作者：
Stephen Friedman;H. Pasula;D. Fox
构建室内环境地图的能力对于自主移动机器人来说极其重要。在本文中，我们介绍了 Voronoi 随机场（VRF），这是一种绘制室内环境拓扑结构的新技术。我们的地图根据空间布局以及有关不同地点及其连通性的信息来描述环境。为了构建这些地图，我们从激光测距仪生成的占用网格地图中提取 Voronoi 图，然后将 Voronoi 图上的每个点表示为条件随机场的节点，这是一个经过判别训练的图形模型。由此产生的 VRF 估计每个节点的标签，集成来自地图和 Voronoi 拓扑的特征。标签提供了环境的分段，不同的分段对应于房间、走廊或门口。使用不同地图的实验表明，我们的技术能够根据从其他环境学到的参数来标记未知环境。
The ability to build maps of indoor environments is extremely important for autonomous mobile robots. In this paper we introduce Voronoi random fields (VRFs), a novel technique for mapping the topological structure of indoor environments. Our maps describe environments in terms of their spatial layout along with information about the different places and their connectivity. To build these maps, we extract a Voronoi graph from an occupancy grid map generated with a laser range-finder, and then represent each point on the Voronoi graph as a node of a conditional random field, which is a discriminatively trained graphical model. The resulting VRF estimates the label of each node, integrating features from both the map and the Voronoi topology. The labels provide a segmentation of an environment, with the different segments corresponding to rooms, hallways, or doorways. Experiments using different maps show that our technique is able to label unknown environments based on parameters learned from other environments.