Todor Stoyanov, Martin Magnusson, Håkan Almqvist and Achim J. Lilienthal
On the Accuracy of the 3D Normal Distributions Transform as a Tool for Spatial Representation
Proc. 2011 IEEE International Conference on Robotics and Automation (ICRA 2011)
Abstract: The Three-Dimensional Normal Distributions Transform (3D-NDT) is a spatial modeling technique with applications in point set registration, scan similarity comparison, change detection and path planning. This work concentrates on evaluating three common variations of the 3D-NDT in terms of accuracy of representing sampled semi-structured environments. In a novel approach to spatial representation quality measurement, the 3D geometrical modeling task is formulated as a classification problem and its accuracy is evaluated with standard machine learning performance metrics. In this manner the accuracy of the 3D-NDT variations is shown to be comparable to, and in some cases to outperform that of the standard occupancy grid mapping model.
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@INPROCEEDINGS{Stoyanov_etal:ICRA:2011,
  AUTHOR = {Stoyanov, Todor and Magnusson, Martin and Almqvist, H\{aa}kan and Lilienthal, Achim J.},
  TITLE = {{On the Accuracy of the 3D Normal Distributions Transform as a Tool for Spatial Representation}},
  BOOKTITLE = {Proceedings of the IEEE International Conference on Robotics and Automation (ICRA)},
  YEAR = {2011},
  MONTH = {May 9--13},
  ADRESS = {Shanghai, China},
  PAGES = {}
}