1. Brunel University Research Archive
  2. College of Engineering, Design and Physical Sciences
  3. Dept of Electronic and Electrical Engineering
  4. Dept of Electronic and Electrical Engineering Embargoed Research Papers
Please use this identifier to cite or link to this item: http://bura.brunel.ac.uk/handle/2438/27447
Full metadata record
DC FieldValueLanguage
dc.contributor.authorYang, Z-
dc.contributor.authorNaz, N-
dc.contributor.authorLiu, P-
dc.contributor.authorHuda, MN-
dc.coverage.spatialCambridge, UK-
dc.date.accessioned2023-10-26T18:25:52Z-
dc.date.available2023-10-26T18:25:52Z-
dc.date.issued2023-09-08-
dc.identifierORCID iD: M. Nazmul Huda https://orcid.org/0000-0002-5376-881X-
dc.identifier.citationYang, Z. et al. (2023) 'Evaluation of SLAM Algorithms for Search and Rescue Applications', in Iida, F. et al. (eds) Towards Autonomous Robotic Systems. TAROS 2023. Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics) vol. 14136 LNAI, pp. 114 - 125. doi: 10.1007/978-3-031-43360-3_10.en_US
dc.identifier.isbn978-3-031-43359-7 (pbk)-
dc.identifier.isbn978-3-031-43360-3 (ebk)-
dc.identifier.issn0302-9743-
dc.identifier.urihttps://bura.brunel.ac.uk/handle/2438/27447-
dc.description.abstractCopyright © 2023 The Author(s). Search and rescue robots have been widely investigated to detect humans in disaster scenarios. SLAM (Simultaneous Localisation and Mapping), as a critical function of the robot, can localise the robot and create the map during the rescue tasks. In this paper, prominent 2D SLAM algorithms are investigated and three of them (Gmapping, Hector, and Karto) are implemented on a low-cost search and rescue robot to demonstrate their feasibility. Moreover, experiments containing various ground surface scenarios are performed. Maps created by various SLAM algorithms are compared to identify the best SLAM algorithm for search and rescue tasks using a low-cost robot. The experimental results suggest that Karto SLAM performs best for low-cost search and rescue robots among the three SLAM algorithms.en_US
dc.format.extent114 - 125-
dc.format.mediumPrint-Electronic-
dc.languageEnglish-
dc.language.isoen_USen_US
dc.publisherSpringer Natureen_US
dc.rightsCopyright © 2023 The Author(s), under exclusive license to Springer Nature Switzerland AG. This version of the article has been accepted for publication, after peer review (when applicable) and is subject to Springer Nature’s AM terms of use (https://www.springernature.com/gp/open-research/policies/book-policies), but is not the Version of Record and does not reflect post-acceptance improvements, or any corrections. The Version of Record is available online at: https://doi.org/10.1007/978-3-031-43360-3_10.-
dc.rights.urihttps://www.springernature.com/gp/open-research/policies/book-policies-
dc.sourceAnnual Conference Towards Autonomous Robotic Systems TAROS 2023-
dc.sourceAnnual Conference Towards Autonomous Robotic Systems TAROS 2023-
dc.subjectsearch and rescueen_US
dc.subjectlow-cost roboten_US
dc.subjectSLAMen_US
dc.subjectKartoen_US
dc.subjectGmappingen_US
dc.titleEvaluation of SLAM Algorithms for Search and Rescue Applicationsen_US
dc.typeConference Paperen_US
dc.identifier.doihttps://doi.org/10.1007/978-3-031-43360-3_10-
dc.relation.isPartOfLecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)-
pubs.finish-date2023-09-15-
pubs.finish-date2023-09-15-
pubs.publication-statusPublished-
pubs.start-date2023-09-13-
pubs.start-date2023-09-13-
pubs.volume14136 LNAI-
dc.identifier.eissn1611-3349-
dc.rights.holderThe Author(s)-
Appears in Collections:Dept of Electronic and Electrical Engineering Embargoed Research Papers

Files in This Item:
File Description SizeFormat 
FullText.pdfEmbargoed until 8 September 2024438.67 kBAdobe PDFView/Open
Show simple item record


Items in BURA are protected by copyright, with all rights reserved, unless otherwise indicated.