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Multi-scale Point and Line Range Data Algorithms for Mapping and Localization

Pfister, Samuel T. and Burdick, Joel W. (2006) Multi-scale Point and Line Range Data Algorithms for Mapping and Localization. In: Proceedings of the 2006 IEEE International Conference on Robotics and Automation. IEEE , Piscataway, NJ, pp. 1159-1166. ISBN 0-7803-9505-0.

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This paper presents a multi-scale point and line based representation of two-dimensional range scan data. The techniques are based on a multi-scale Hough transform and a tree representation of the environment’s features. The multiscale representation can lead to improved robustness and computational efficiencies in basic operations, such as matching and correspondence, that commonly arise in many localization and mapping procedures. For multi-scale matching and correspondence we introduce a χ^2 criterion that is calculated from the estimated variance in position of each detected line segment or point. This improved correspondence method can be used as the basis for simple scan-matching displacement estimation, as a part of a SLAM implementation, or as the basis for solutions to the kidnapped robot problem. Experimental results (using a Sick LMS-200 range scanner) show the effectiveness of our methods.

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Additional Information:© 2006 IEEE. Issue Date: 15-19 May 2006; Date of Current Version: 26 June 2006. This research has was sponsored in part by a National Science Foundation Engineering Research Center grant (NSF9402726) and NSF ERC-CREST partnership award EEC-9730980.
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European Research Council (ERC)UNSPECIFIED
Record Number:CaltechAUTHORS:20110121-100516594
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Official Citation:Pfister, S.T.; Burdick, J.W.; , "Multi-scale point and line range data algorithms for mapping and localization," Robotics and Automation, 2006. ICRA 2006. Proceedings 2006 IEEE International Conference on , vol., no., pp.1159-1166, 15-19 May 2006 doi: 10.1109/ROBOT.2006.1641866 URL:
Usage Policy:No commercial reproduction, distribution, display or performance rights in this work are provided.
ID Code:21847
Deposited On:24 Jan 2011 18:16
Last Modified:09 Nov 2021 16:00

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