Scan Matching by Cross-Correlation and Differential Evolution
Scan matching is an important task, solved in the context of many high-level problems including pose estimation, indoor localization, simultaneous localization and mapping and others. Methods that are accurate and adaptive and at the same time computationally efficient are required to enable locatio...
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doaj-c83b309aa3f8429497cefd4a9e93bc442020-11-25T01:14:04ZengMDPI AGElectronics2079-92922019-08-018885610.3390/electronics8080856electronics8080856Scan Matching by Cross-Correlation and Differential EvolutionJaromir Konecny0Pavel Kromer1Michal Prauzek2Petr Musilek3Faculty of Electrical Engineering and Computer Science, VSB—Technical University of Ostrava, 708 00 Ostrava, Czech RepublicFaculty of Electrical Engineering and Computer Science, VSB—Technical University of Ostrava, 708 00 Ostrava, Czech RepublicFaculty of Electrical Engineering and Computer Science, VSB—Technical University of Ostrava, 708 00 Ostrava, Czech RepublicDepartment of Electrical and Computer Engineering, University of Alberta, Edmonton, AB T6G 1H9, CanadaScan matching is an important task, solved in the context of many high-level problems including pose estimation, indoor localization, simultaneous localization and mapping and others. Methods that are accurate and adaptive and at the same time computationally efficient are required to enable location-based services in autonomous mobile devices. Such devices usually have a wide range of high-resolution sensors but only a limited processing power and constrained energy supply. This work introduces a novel high-level scan matching strategy that uses a combination of two advanced algorithms recently used in this field: cross-correlation and differential evolution. The cross-correlation between two laser range scans is used as an efficient measure of scan alignment and the differential evolution algorithm is used to search for the parameters of a transformation that aligns the scans. The proposed method was experimentally validated and showed good ability to match laser range scans taken shortly after each other and an excellent ability to match laser range scans taken with longer time intervals between them.https://www.mdpi.com/2079-9292/8/8/856scan matchingindoor localizationdifferential evolutioncross-correlationrobotics |
collection |
DOAJ |
language |
English |
format |
Article |
sources |
DOAJ |
author |
Jaromir Konecny Pavel Kromer Michal Prauzek Petr Musilek |
spellingShingle |
Jaromir Konecny Pavel Kromer Michal Prauzek Petr Musilek Scan Matching by Cross-Correlation and Differential Evolution Electronics scan matching indoor localization differential evolution cross-correlation robotics |
author_facet |
Jaromir Konecny Pavel Kromer Michal Prauzek Petr Musilek |
author_sort |
Jaromir Konecny |
title |
Scan Matching by Cross-Correlation and Differential Evolution |
title_short |
Scan Matching by Cross-Correlation and Differential Evolution |
title_full |
Scan Matching by Cross-Correlation and Differential Evolution |
title_fullStr |
Scan Matching by Cross-Correlation and Differential Evolution |
title_full_unstemmed |
Scan Matching by Cross-Correlation and Differential Evolution |
title_sort |
scan matching by cross-correlation and differential evolution |
publisher |
MDPI AG |
series |
Electronics |
issn |
2079-9292 |
publishDate |
2019-08-01 |
description |
Scan matching is an important task, solved in the context of many high-level problems including pose estimation, indoor localization, simultaneous localization and mapping and others. Methods that are accurate and adaptive and at the same time computationally efficient are required to enable location-based services in autonomous mobile devices. Such devices usually have a wide range of high-resolution sensors but only a limited processing power and constrained energy supply. This work introduces a novel high-level scan matching strategy that uses a combination of two advanced algorithms recently used in this field: cross-correlation and differential evolution. The cross-correlation between two laser range scans is used as an efficient measure of scan alignment and the differential evolution algorithm is used to search for the parameters of a transformation that aligns the scans. The proposed method was experimentally validated and showed good ability to match laser range scans taken shortly after each other and an excellent ability to match laser range scans taken with longer time intervals between them. |
topic |
scan matching indoor localization differential evolution cross-correlation robotics |
url |
https://www.mdpi.com/2079-9292/8/8/856 |
work_keys_str_mv |
AT jaromirkonecny scanmatchingbycrosscorrelationanddifferentialevolution AT pavelkromer scanmatchingbycrosscorrelationanddifferentialevolution AT michalprauzek scanmatchingbycrosscorrelationanddifferentialevolution AT petrmusilek scanmatchingbycrosscorrelationanddifferentialevolution |
_version_ |
1725159139755163648 |