Scan registration for autonomous mining vehicles using 3D-NDT
Scan registration for autonomous mining vehicles using 3D-NDT
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DOI：
10.1002/rob.20204
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发表时间：
2007-10-01
影响因子：
8.3
通讯作者：
Duckett, Tom
中科院分区：
文献类型：
--
作者：
Magnusson, Martin;Lilienthal, Achim;Duckett, Tom
扫描注册是一个必不可少的子任务时，建立地图的基础上测距数据从移动的机器人。问题是根据扫描重叠部分的形状来推断机器人在连续扫描之间是如何移动的。本文提出了一种新的三维数据配准算法。该算法是Biber和Strasser开发的2D数据的正态分布变换（NDT）的推广和改进，其允许使用扫描表面的存储器高效表示进行精确配准。一个详细的定量和定性的新算法与流行的ICP（迭代最近点）算法的3D版本的比较。与实际的矿山数据，其中一些收集了一个新的原型3D激光扫描仪的结果表明，所提出的算法是更快，比标准的ICP算法的3D配准更可靠，同时使用更节省内存的扫描表面表示。(C)2007 Wiley Periodicals，Inc.
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. (C) 2007 Wiley Periodicals, Inc.