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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Main Authors: Jaromir Konecny, Pavel Kromer, Michal Prauzek, Petr Musilek
Format: Article
Language:English
Published: MDPI AG 2019-08-01
Series:Electronics
Subjects:
Online Access:https://www.mdpi.com/2079-9292/8/8/856
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spelling 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
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