Loading…
Performance of Different SLAM Algorithms for Indoor and Outdoor Mapping Applications
Indoor and outdoor mapping studies can be completed relatively quickly, depending on the developments in Mobile Mapping Systems. Especially in indoor environments where high accuracy GNSS positions cannot be used, mapping studies can be carried out with SLAM algorithms. Although there are many diffe...
Saved in:
Published in: | Applied system innovation 2021-12, Vol.4 (4), p.101 |
---|---|
Main Author: | |
Format: | Article |
Language: | English |
Subjects: | |
Citations: | Items that this one cites Items that cite this one |
Online Access: | Get full text |
Tags: |
Add Tag
No Tags, Be the first to tag this record!
|
cited_by | cdi_FETCH-LOGICAL-c361t-33f4a4be441aa839aef153ec976a53acd8a522ffb56a3fbc27ecfb40bb6759633 |
---|---|
cites | cdi_FETCH-LOGICAL-c361t-33f4a4be441aa839aef153ec976a53acd8a522ffb56a3fbc27ecfb40bb6759633 |
container_end_page | |
container_issue | 4 |
container_start_page | 101 |
container_title | Applied system innovation |
container_volume | 4 |
creator | Akpınar, Burak |
description | Indoor and outdoor mapping studies can be completed relatively quickly, depending on the developments in Mobile Mapping Systems. Especially in indoor environments where high accuracy GNSS positions cannot be used, mapping studies can be carried out with SLAM algorithms. Although there are many different SLAM algorithms in the literature, each can produce results with different accuracy according to the mapped environment. In this study, 3D maps were produced with LOAM, A-LOAM, and HDL Graph SLAM algorithms in different environments such as long corridors, staircases, and outdoor environments, and the accuracies of the maps produced with different algorithms were compared. For this purpose, a mobile mapping platform using Velodyne VLP-16 LIDAR sensor was developed, and the odometer drift, which causes loss of accuracy in the data collected, was minimized by loop closure and plane detection methods. As a result of the tests, it was determined that the results of the LOAM algorithm were not as accurate as those of the A-LOAM and HDL Graph SLAM algorithms. Both indoor and outdoor environments and the A-LOAM results’ accuracy were two times better than HDL Graph SLAM results. |
doi_str_mv | 10.3390/asi4040101 |
format | article |
fullrecord | <record><control><sourceid>proquest_doaj_</sourceid><recordid>TN_cdi_doaj_primary_oai_doaj_org_article_4f975d01ac2a40a998a49a25c4b49e4a</recordid><sourceformat>XML</sourceformat><sourcesystem>PC</sourcesystem><doaj_id>oai_doaj_org_article_4f975d01ac2a40a998a49a25c4b49e4a</doaj_id><sourcerecordid>2612730642</sourcerecordid><originalsourceid>FETCH-LOGICAL-c361t-33f4a4be441aa839aef153ec976a53acd8a522ffb56a3fbc27ecfb40bb6759633</originalsourceid><addsrcrecordid>eNpNkUtLAzEUhYMoWLQbf0HAnVDNc9Ish_oqtFSwrsOdTFJTppMxmS78946tqKtzuHycc-EgdEXJLeea3EEOgghCCT1BIyYVnUip1Ok_f47GOW8JIUxpLokeofWLSz6mHbTW4ejxffDeJdf2-HVRLnHZbGIK_fsu44HC87aOg0Bb49W-P_gldF1oN7jsuiZY6ENs8yU689BkN_7RC_T2-LCePU8Wq6f5rFxMLC9oP-HcCxCVE4ICTLkG56nkzmpVgORg6ylIxryvZAHcV5YpZ30lSFUVSuqC8ws0P-bWEbamS2EH6dNECOZwiGljIPXBNs4Ir5WsCQXLQBDQegpCA5NWVEI7AUPW9TGrS_Fj73JvtnGf2uF9wwrKFCeFYAN1c6Rsijkn539bKTHfI5i_EfgXvfx5Tg</addsrcrecordid><sourcetype>Open Website</sourcetype><iscdi>true</iscdi><recordtype>article</recordtype><pqid>2612730642</pqid></control><display><type>article</type><title>Performance of Different SLAM Algorithms for Indoor and Outdoor Mapping Applications</title><source>Publicly Available Content Database</source><creator>Akpınar, Burak</creator><creatorcontrib>Akpınar, Burak</creatorcontrib><description>Indoor and outdoor mapping studies can be completed relatively quickly, depending on the developments in Mobile Mapping Systems. Especially in indoor environments where high accuracy GNSS positions cannot be used, mapping studies can be carried out with SLAM algorithms. Although there are many different SLAM algorithms in the literature, each can produce results with different accuracy according to the mapped environment. In this study, 3D maps were produced with LOAM, A-LOAM, and HDL Graph SLAM algorithms in different environments such as long corridors, staircases, and outdoor environments, and the accuracies of the maps produced with different algorithms were compared. For this purpose, a mobile mapping platform using Velodyne VLP-16 LIDAR sensor was developed, and the odometer drift, which causes loss of accuracy in the data collected, was minimized by loop closure and plane detection methods. As a result of the tests, it was determined that the results of the LOAM algorithm were not as accurate as those of the A-LOAM and HDL Graph SLAM algorithms. Both indoor and outdoor environments and the A-LOAM results’ accuracy were two times better than HDL Graph SLAM results.</description><identifier>ISSN: 2571-5577</identifier><identifier>EISSN: 2571-5577</identifier><identifier>DOI: 10.3390/asi4040101</identifier><language>eng</language><publisher>Basel: MDPI AG</publisher><subject>Accuracy ; Algorithms ; Cartography ; Corridors ; Indoor environments ; indoor mapping ; LIDAR ; Loam ; Localization ; Mapping ; Methods ; outdoor mapping ; Robots ; Sensors ; SLAM ; Staircases ; Velocity</subject><ispartof>Applied system innovation, 2021-12, Vol.4 (4), p.101</ispartof><rights>2021 by the author. Licensee MDPI, Basel, Switzerland. This article is an open access article distributed under the terms and conditions of the Creative Commons Attribution (CC BY) license (https://creativecommons.org/licenses/by/4.0/). Notwithstanding the ProQuest Terms and Conditions, you may use this content in accordance with the terms of the License.</rights><lds50>peer_reviewed</lds50><oa>free_for_read</oa><woscitedreferencessubscribed>false</woscitedreferencessubscribed><citedby>FETCH-LOGICAL-c361t-33f4a4be441aa839aef153ec976a53acd8a522ffb56a3fbc27ecfb40bb6759633</citedby><cites>FETCH-LOGICAL-c361t-33f4a4be441aa839aef153ec976a53acd8a522ffb56a3fbc27ecfb40bb6759633</cites><orcidid>0000-0002-3076-1578</orcidid></display><links><openurl>$$Topenurl_article</openurl><openurlfulltext>$$Topenurlfull_article</openurlfulltext><thumbnail>$$Tsyndetics_thumb_exl</thumbnail><linktopdf>$$Uhttps://www.proquest.com/docview/2612730642/fulltextPDF?pq-origsite=primo$$EPDF$$P50$$Gproquest$$Hfree_for_read</linktopdf><linktohtml>$$Uhttps://www.proquest.com/docview/2612730642?pq-origsite=primo$$EHTML$$P50$$Gproquest$$Hfree_for_read</linktohtml><link.rule.ids>314,780,784,25753,27924,27925,37012,44590,75126</link.rule.ids></links><search><creatorcontrib>Akpınar, Burak</creatorcontrib><title>Performance of Different SLAM Algorithms for Indoor and Outdoor Mapping Applications</title><title>Applied system innovation</title><description>Indoor and outdoor mapping studies can be completed relatively quickly, depending on the developments in Mobile Mapping Systems. Especially in indoor environments where high accuracy GNSS positions cannot be used, mapping studies can be carried out with SLAM algorithms. Although there are many different SLAM algorithms in the literature, each can produce results with different accuracy according to the mapped environment. In this study, 3D maps were produced with LOAM, A-LOAM, and HDL Graph SLAM algorithms in different environments such as long corridors, staircases, and outdoor environments, and the accuracies of the maps produced with different algorithms were compared. For this purpose, a mobile mapping platform using Velodyne VLP-16 LIDAR sensor was developed, and the odometer drift, which causes loss of accuracy in the data collected, was minimized by loop closure and plane detection methods. As a result of the tests, it was determined that the results of the LOAM algorithm were not as accurate as those of the A-LOAM and HDL Graph SLAM algorithms. Both indoor and outdoor environments and the A-LOAM results’ accuracy were two times better than HDL Graph SLAM results.</description><subject>Accuracy</subject><subject>Algorithms</subject><subject>Cartography</subject><subject>Corridors</subject><subject>Indoor environments</subject><subject>indoor mapping</subject><subject>LIDAR</subject><subject>Loam</subject><subject>Localization</subject><subject>Mapping</subject><subject>Methods</subject><subject>outdoor mapping</subject><subject>Robots</subject><subject>Sensors</subject><subject>SLAM</subject><subject>Staircases</subject><subject>Velocity</subject><issn>2571-5577</issn><issn>2571-5577</issn><fulltext>true</fulltext><rsrctype>article</rsrctype><creationdate>2021</creationdate><recordtype>article</recordtype><sourceid>PIMPY</sourceid><sourceid>DOA</sourceid><recordid>eNpNkUtLAzEUhYMoWLQbf0HAnVDNc9Ish_oqtFSwrsOdTFJTppMxmS78946tqKtzuHycc-EgdEXJLeea3EEOgghCCT1BIyYVnUip1Ok_f47GOW8JIUxpLokeofWLSz6mHbTW4ejxffDeJdf2-HVRLnHZbGIK_fsu44HC87aOg0Bb49W-P_gldF1oN7jsuiZY6ENs8yU689BkN_7RC_T2-LCePU8Wq6f5rFxMLC9oP-HcCxCVE4ICTLkG56nkzmpVgORg6ylIxryvZAHcV5YpZ30lSFUVSuqC8ws0P-bWEbamS2EH6dNECOZwiGljIPXBNs4Ir5WsCQXLQBDQegpCA5NWVEI7AUPW9TGrS_Fj73JvtnGf2uF9wwrKFCeFYAN1c6Rsijkn539bKTHfI5i_EfgXvfx5Tg</recordid><startdate>20211201</startdate><enddate>20211201</enddate><creator>Akpınar, Burak</creator><general>MDPI AG</general><scope>AAYXX</scope><scope>CITATION</scope><scope>8FE</scope><scope>8FG</scope><scope>ABJCF</scope><scope>ABUWG</scope><scope>AFKRA</scope><scope>ARAPS</scope><scope>AZQEC</scope><scope>BENPR</scope><scope>BGLVJ</scope><scope>CCPQU</scope><scope>DWQXO</scope><scope>HCIFZ</scope><scope>L6V</scope><scope>M7S</scope><scope>P5Z</scope><scope>P62</scope><scope>PIMPY</scope><scope>PQEST</scope><scope>PQQKQ</scope><scope>PQUKI</scope><scope>PRINS</scope><scope>PTHSS</scope><scope>DOA</scope><orcidid>https://orcid.org/0000-0002-3076-1578</orcidid></search><sort><creationdate>20211201</creationdate><title>Performance of Different SLAM Algorithms for Indoor and Outdoor Mapping Applications</title><author>Akpınar, Burak</author></sort><facets><frbrtype>5</frbrtype><frbrgroupid>cdi_FETCH-LOGICAL-c361t-33f4a4be441aa839aef153ec976a53acd8a522ffb56a3fbc27ecfb40bb6759633</frbrgroupid><rsrctype>articles</rsrctype><prefilter>articles</prefilter><language>eng</language><creationdate>2021</creationdate><topic>Accuracy</topic><topic>Algorithms</topic><topic>Cartography</topic><topic>Corridors</topic><topic>Indoor environments</topic><topic>indoor mapping</topic><topic>LIDAR</topic><topic>Loam</topic><topic>Localization</topic><topic>Mapping</topic><topic>Methods</topic><topic>outdoor mapping</topic><topic>Robots</topic><topic>Sensors</topic><topic>SLAM</topic><topic>Staircases</topic><topic>Velocity</topic><toplevel>peer_reviewed</toplevel><toplevel>online_resources</toplevel><creatorcontrib>Akpınar, Burak</creatorcontrib><collection>CrossRef</collection><collection>ProQuest SciTech Collection</collection><collection>ProQuest Technology Collection</collection><collection>Materials Science & Engineering Collection</collection><collection>ProQuest Central (Alumni)</collection><collection>ProQuest Central</collection><collection>Advanced Technologies & Aerospace Database (1962 - current)</collection><collection>ProQuest Central Essentials</collection><collection>AUTh Library subscriptions: ProQuest Central</collection><collection>Technology Collection</collection><collection>ProQuest One Community College</collection><collection>ProQuest Central Korea</collection><collection>SciTech Premium Collection (Proquest) (PQ_SDU_P3)</collection><collection>ProQuest Engineering Collection</collection><collection>Engineering Database</collection><collection>ProQuest advanced technologies & aerospace journals</collection><collection>ProQuest Advanced Technologies & Aerospace Collection</collection><collection>Publicly Available Content Database</collection><collection>ProQuest One Academic Eastern Edition (DO NOT USE)</collection><collection>ProQuest One Academic</collection><collection>ProQuest One Academic UKI Edition</collection><collection>ProQuest Central China</collection><collection>Engineering collection</collection><collection>DOAJ Directory of Open Access Journals</collection><jtitle>Applied system innovation</jtitle></facets><delivery><delcategory>Remote Search Resource</delcategory><fulltext>fulltext</fulltext></delivery><addata><au>Akpınar, Burak</au><format>journal</format><genre>article</genre><ristype>JOUR</ristype><atitle>Performance of Different SLAM Algorithms for Indoor and Outdoor Mapping Applications</atitle><jtitle>Applied system innovation</jtitle><date>2021-12-01</date><risdate>2021</risdate><volume>4</volume><issue>4</issue><spage>101</spage><pages>101-</pages><issn>2571-5577</issn><eissn>2571-5577</eissn><abstract>Indoor and outdoor mapping studies can be completed relatively quickly, depending on the developments in Mobile Mapping Systems. Especially in indoor environments where high accuracy GNSS positions cannot be used, mapping studies can be carried out with SLAM algorithms. Although there are many different SLAM algorithms in the literature, each can produce results with different accuracy according to the mapped environment. In this study, 3D maps were produced with LOAM, A-LOAM, and HDL Graph SLAM algorithms in different environments such as long corridors, staircases, and outdoor environments, and the accuracies of the maps produced with different algorithms were compared. For this purpose, a mobile mapping platform using Velodyne VLP-16 LIDAR sensor was developed, and the odometer drift, which causes loss of accuracy in the data collected, was minimized by loop closure and plane detection methods. As a result of the tests, it was determined that the results of the LOAM algorithm were not as accurate as those of the A-LOAM and HDL Graph SLAM algorithms. Both indoor and outdoor environments and the A-LOAM results’ accuracy were two times better than HDL Graph SLAM results.</abstract><cop>Basel</cop><pub>MDPI AG</pub><doi>10.3390/asi4040101</doi><orcidid>https://orcid.org/0000-0002-3076-1578</orcidid><oa>free_for_read</oa></addata></record> |
fulltext | fulltext |
identifier | ISSN: 2571-5577 |
ispartof | Applied system innovation, 2021-12, Vol.4 (4), p.101 |
issn | 2571-5577 2571-5577 |
language | eng |
recordid | cdi_doaj_primary_oai_doaj_org_article_4f975d01ac2a40a998a49a25c4b49e4a |
source | Publicly Available Content Database |
subjects | Accuracy Algorithms Cartography Corridors Indoor environments indoor mapping LIDAR Loam Localization Mapping Methods outdoor mapping Robots Sensors SLAM Staircases Velocity |
title | Performance of Different SLAM Algorithms for Indoor and Outdoor Mapping Applications |
url | http://sfxeu10.hosted.exlibrisgroup.com/loughborough?ctx_ver=Z39.88-2004&ctx_enc=info:ofi/enc:UTF-8&ctx_tim=2025-01-01T12%3A14%3A39IST&url_ver=Z39.88-2004&url_ctx_fmt=infofi/fmt:kev:mtx:ctx&rfr_id=info:sid/primo.exlibrisgroup.com:primo3-Article-proquest_doaj_&rft_val_fmt=info:ofi/fmt:kev:mtx:journal&rft.genre=article&rft.atitle=Performance%20of%20Different%20SLAM%20Algorithms%20for%20Indoor%20and%20Outdoor%20Mapping%20Applications&rft.jtitle=Applied%20system%20innovation&rft.au=Akp%C4%B1nar,%20Burak&rft.date=2021-12-01&rft.volume=4&rft.issue=4&rft.spage=101&rft.pages=101-&rft.issn=2571-5577&rft.eissn=2571-5577&rft_id=info:doi/10.3390/asi4040101&rft_dat=%3Cproquest_doaj_%3E2612730642%3C/proquest_doaj_%3E%3Cgrp_id%3Ecdi_FETCH-LOGICAL-c361t-33f4a4be441aa839aef153ec976a53acd8a522ffb56a3fbc27ecfb40bb6759633%3C/grp_id%3E%3Coa%3E%3C/oa%3E%3Curl%3E%3C/url%3E&rft_id=info:oai/&rft_pqid=2612730642&rft_id=info:pmid/&rfr_iscdi=true |