Scan registration for autonomous mining vehicles using 3D-NDT: Research Articles

Authors:
Martin Magnusson;Achim Lilienthal;Tom Duckett
Affiliations:
AASS Department of Technology Örebro University SE-701 82 Örebro, Sweden;AASS Department of Technology Örebro University SE-701 82 Örebro, Sweden;Department of Computing and Informatics University of Lincoln Brayford Pool Lincoln LN6 7TS UK
Venue:
Journal of Field Robotics - Special Issue on Mining Robotics
Year:
2007

Citing 0
Cited 19

HSM3D: feature-less global 6DOF scan-matching in the Hough/Radon domain

ICRA'09 Proceedings of the 2009 IEEE international conference on Robotics and Automation
Evaluation of 3D registration reliability and speed: a comparison of ICP and NDT

ICRA'09 Proceedings of the 2009 IEEE international conference on Robotics and Automation
Appearance-based loop detection from 3D laser data using the normal distributions transform

ICRA'09 Proceedings of the 2009 IEEE international conference on Robotics and Automation
6D scan registration using depth-interpolated local image features

Robotics and Autonomous Systems
An experimental assessment of the HSM3D algorithm for sparse and colored data

IROS'09 Proceedings of the 2009 IEEE/RSJ international conference on Intelligent robots and systems
Fast 3D mapping by matching planes extracted from range sensor point-clouds

IROS'09 Proceedings of the 2009 IEEE/RSJ international conference on Intelligent robots and systems
Fast registration based on noisy planes with unknown correspondences for 3-D mapping

IEEE Transactions on Robotics
Semantic simulation engine for supervision of mobile robotic system

ICCCI'11 Proceedings of the Third international conference on Computational collective intelligence: technologies and applications - Volume Part II
Learning to close loops from range data

International Journal of Robotics Research
Visual SLAM Based on Rigid-Body 3D Landmarks

Journal of Intelligent and Robotic Systems
Tuning stereo image matching with stereo video sequence processing

Proceedings of the 2012 Joint International Conference on Human-Centered Computer Environments
Three-dimensional SLAM for mapping planetary work site environments

Journal of Field Robotics
A landmark-bounded method for large-scale underground mine mapping

Journal of Field Robotics
OctoMap: an efficient probabilistic 3D mapping framework based on octrees

Autonomous Robots
Comparing ICP variants on real-world data sets

Autonomous Robots
Comparative evaluation of range sensor accuracy for indoor mobile robotics and automated logistics applications

Robotics and Autonomous Systems
Three-dimensional point cloud plane segmentation in both structured and unstructured environments

Robotics and Autonomous Systems
3D normal distributions transform occupancy maps: An efficient representation for mapping in dynamic environments

International Journal of Robotics Research
Multi-resolution surfel maps for efficient dense 3D modeling and tracking

Journal of Visual Communication and Image Representation

Quantified Score

Hi-index	0.00

Visualization

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. © 2007 Wiley Periodicals, Inc.