Using Hierarchical EM to Extract Planes from 3D Range Scans
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Recently, the acquisition of three-dimensional maps has become more and more popular. This is motivated by the fact that robots act in the three-dimensional world and several tasks such as path planning or localizing objects can be carried out more reliable using three-dimensional representations. In this paper we consider the problem of extracting planes from three-dimensional range data. In contrast to previous approaches our algorithm uses a hierarchical variant of the popular Expectation Maximization (EM) algorithm  to simultaneously learn the main directions of the planar structures. These main directions are then used to correct the position and orientation of planes. In practical experiments carried out with real data and in simulations we demonstrate that our algorithm can accurately extract planes and their orientation from range data.