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Mobile Information Systems
Volume 2016, Article ID 6463945, 11 pages
Research Article

Novel Point-to-Point Scan Matching Algorithm Based on Cross-Correlation

1Department of Cybernetics and Biomedical Engineering, VSB-Technical University of Ostrava, 17. Listopadu 2172/15, 70833 Ostrava, Czech Republic
2Department of Computer Science, VSB-Technical University of Ostrava, 17. Listopadu 2172/15, 70833 Ostrava, Czech Republic
3Department of Electrical and Computer Engineering, Faculty of Engineering, University of Alberta, 9107-116 Street, Edmonton, AB, Canada T6G 2V4

Received 4 February 2016; Accepted 5 April 2016

Academic Editor: Peter Brida

Copyright © 2016 Jaromir Konecny et al. This is an open access article distributed under the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.


The localization of mobile robots in outdoor and indoor environments is a complex issue. Many sophisticated approaches, based on various types of sensory inputs and different computational concepts, are used to accomplish this task. However, many of the most efficient methods for mobile robot localization suffer from high computational costs and/or the need for high resolution sensory inputs. Scan cross-correlation is a traditional approach that can be, in special cases, used to match temporally aligned scans of robot environment. This work proposes a set of novel modifications to the cross-correlation method that extend its capability beyond these special cases to general scan matching and mitigate its computational costs so that it is usable in practical settings. The properties and validity of the proposed approach are in this study illustrated on a number of computational experiments.