Scan registration for autonomous mining vehicles using 3D-NDT

Magnusson, Martin and Lilienthals, Achim and Duckett, Tom (2007) Scan registration for autonomous mining vehicles using 3D-NDT. Journal of Field Robotics, 24 (10). pp. 803-827. ISSN 1556-4959

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Scan Registration for Autonomous Mining Vehicles Using 3D-NDT
Martin Magnusson, Achim Lilienthal and Tom Duckett. Scan Registration for Autonomous Mining Vehicles Using 3D-NDT. Journal of Field Robotics, Vol. 24 (10), pp. 803-827, 2007.
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Abstract

Scan registration is an essential subtask when building maps based on range finder data from mobile robots. The problem is to deduce how the robot has moved between consecutive scans, based on the shape of overlapping portions of the scans. This paper presents a new algorithm for registration of 3D data. The algorithm is a generalization and improvement of the normal distributions transform (NDT) for 2D data developed by Biber and Strasser, which allows for accurate registration using a memory-efficient representation of the scan surface. A detailed quantitative and qualitative comparison of the new algorithm with the 3D version of the popular ICP (iterative closest point) algorithm is presented. Results with actual mine data, some of which were collected with a new prototype 3D laser scanner, show that the presented algorithm is faster and slightly more reliable than the standard ICP algorithm for 3D registration, while using a more memory efficient scan surface representation.

Item Type:Article
Additional Information:Scan registration is an essential subtask when building maps based on range finder data from mobile robots. The problem is to deduce how the robot has moved between consecutive scans, based on the shape of overlapping portions of the scans. This paper presents a new algorithm for registration of 3D data. The algorithm is a generalization and improvement of the normal distributions transform (NDT) for 2D data developed by Biber and Strasser, which allows for accurate registration using a memory-efficient representation of the scan surface. A detailed quantitative and qualitative comparison of the new algorithm with the 3D version of the popular ICP (iterative closest point) algorithm is presented. Results with actual mine data, some of which were collected with a new prototype 3D laser scanner, show that the presented algorithm is faster and slightly more reliable than the standard ICP algorithm for 3D registration, while using a more memory efficient scan surface representation.
Keywords:mobile robotics, scan registration, SLAM, 3d mapping, navigation
Subjects:G Mathematical and Computer Sciences > G700 Artificial Intelligence
G Mathematical and Computer Sciences > G400 Computer Science
H Engineering > H671 Robotics
Divisions:College of Science > School of Computer Science
ID Code:1615
Deposited By: Tom Duckett
Deposited On:17 Jul 2008 06:11
Last Modified:13 Mar 2013 08:29

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