METHOD OF SIMULTANEOUS LOCALIZATION AND MAPPING FOR CONSTRUCTION OF 2.5D MAPS OF THE ENVIRONMENT USING ROS

SLAM (Simultaneous Localization and Mapping) is a relevant topic of research and development in the field of robotics and computer vision. SLAM finds wide applications in various areas such as autonomous navigation of intelligent robots, solving problems in augmented and virtual reality, UAVs, and o...

Full description

Saved in:
Bibliographic Details
Published in:Sučasnij stan naukovih doslìdženʹ ta tehnologìj v promislovostì (Online) no. 2 (24); pp. 145 - 160
Main Authors: Nevlyudov, Igor, Novoselov, Sergiy, Sukhachov, Konstantin
Format: Journal Article
Language:English
Published: 05.08.2023
ISSN:2522-9818, 2524-2296
Online Access:Get full text
Tags: Add Tag
No Tags, Be the first to tag this record!
Abstract SLAM (Simultaneous Localization and Mapping) is a relevant topic of research and development in the field of robotics and computer vision. SLAM finds wide applications in various areas such as autonomous navigation of intelligent robots, solving problems in augmented and virtual reality, UAVs, and other systems. In recent years, SLAM has made significant progress due to the gradual development of its algorithms, the use of advanced sensors, and improvements in computational power of computers. The subject of this study is modern methods of real-time simultaneous localization and mapping. The goal of the research is to model the developed algorithm for constructing maps of the surrounding environment and determining the position and orientation of the intelligent robot in space in real-time using ROS packages. The purpose of this article is to demonstrate the results of combining SLAM methods and developing new approaches to solve simultaneous localization and mapping problems. In order to achieve the set objectives, a collaboration of laser scanning (2D LRF) and depth image reconstruction (RGB-D) methods was utilized for simultaneous localization and mapping of the intelligent robot and construction of a 2.5D environment map. The obtained results are promising and demonstrate the potential of the integrated SLAM methods, which collaborate to ensure accurate execution of simultaneous localization and mapping for intelligent robots in real-time mode. The proposed method allows for considering obstacle heights in constructing the map of the surrounding environment while requiring less computational power. In conclusion, this approach expands technologies without replacing existing working propositions and enables the use of modern methods for comprehensive detection and recognition of the surrounding environment through an efficient localization and mapping approach, providing more accurate results with fewer resources utilized.
AbstractList SLAM (Simultaneous Localization and Mapping) is a relevant topic of research and development in the field of robotics and computer vision. SLAM finds wide applications in various areas such as autonomous navigation of intelligent robots, solving problems in augmented and virtual reality, UAVs, and other systems. In recent years, SLAM has made significant progress due to the gradual development of its algorithms, the use of advanced sensors, and improvements in computational power of computers. The subject of this study is modern methods of real-time simultaneous localization and mapping. The goal of the research is to model the developed algorithm for constructing maps of the surrounding environment and determining the position and orientation of the intelligent robot in space in real-time using ROS packages. The purpose of this article is to demonstrate the results of combining SLAM methods and developing new approaches to solve simultaneous localization and mapping problems. In order to achieve the set objectives, a collaboration of laser scanning (2D LRF) and depth image reconstruction (RGB-D) methods was utilized for simultaneous localization and mapping of the intelligent robot and construction of a 2.5D environment map. The obtained results are promising and demonstrate the potential of the integrated SLAM methods, which collaborate to ensure accurate execution of simultaneous localization and mapping for intelligent robots in real-time mode. The proposed method allows for considering obstacle heights in constructing the map of the surrounding environment while requiring less computational power. In conclusion, this approach expands technologies without replacing existing working propositions and enables the use of modern methods for comprehensive detection and recognition of the surrounding environment through an efficient localization and mapping approach, providing more accurate results with fewer resources utilized.
Author Sukhachov, Konstantin
Nevlyudov, Igor
Novoselov, Sergiy
Author_xml – sequence: 1
  givenname: Igor
  orcidid: 0000-0002-9837-2309
  surname: Nevlyudov
  fullname: Nevlyudov, Igor
– sequence: 2
  givenname: Sergiy
  orcidid: 0000-0002-3190-0592
  surname: Novoselov
  fullname: Novoselov, Sergiy
– sequence: 3
  givenname: Konstantin
  orcidid: 0009-0005-2277-9822
  surname: Sukhachov
  fullname: Sukhachov, Konstantin
BookMark eNotkM1ugzAQhK0qlZqmeYGe_AJQ7xqCfUSEJJbAjrDpoRfEr9SoTSo49e2bkJ52VjOzK33PZHG-nHtCXoH5nAkevSlnrfKRIfcx8CEIH8gSQww8RLlZzBo9KUA8kfU0nRhjKKINQ1iSU566g9lSs6NW5WXmYp2a0tLMJHGmPmKnjKax3tI8Ph6V3tOdKWhitHVFmczmtYl-OAfsbXGHlKb6XRVG56l2tLS3WmHsC3kc6q-pX__PFbG71CUHLzN7df3mtSIKPSFBhnIAaJueyb6vBR86tqm7sGlrDpwBILAWGgFRJxvWQY1dJAMOsgMx8BXB-9V2vEzT2A_Vz_j5XY-_FbBqxlXNuKobrgqD6oqL_wG1KlZL
ContentType Journal Article
DBID AAYXX
CITATION
DOI 10.30837/ITSSI.2023.24.145
DatabaseName CrossRef
DatabaseTitle CrossRef
DatabaseTitleList CrossRef
DeliveryMethod fulltext_linktorsrc
Discipline Business
EISSN 2524-2296
EndPage 160
ExternalDocumentID 10_30837_ITSSI_2023_24_145
GroupedDBID AAYXX
ADBBV
ALMA_UNASSIGNED_HOLDINGS
BCNDV
CITATION
GROUPED_DOAJ
ID FETCH-LOGICAL-c875-891959f11cbe09eea83fd06ad5bca313011210c1b817d9b0d1a2d794319d18f3
ISSN 2522-9818
IngestDate Sat Nov 29 06:22:14 EST 2025
IsDoiOpenAccess false
IsOpenAccess true
IsPeerReviewed true
IsScholarly true
Issue 2 (24)
Language English
License http://creativecommons.org/licenses/by-nc-sa/4.0
LinkModel OpenURL
MergedId FETCHMERGED-LOGICAL-c875-891959f11cbe09eea83fd06ad5bca313011210c1b817d9b0d1a2d794319d18f3
ORCID 0000-0002-9837-2309
0009-0005-2277-9822
0000-0002-3190-0592
OpenAccessLink https://journals.uran.ua/itssi/article/download/285517/279577
PageCount 16
ParticipantIDs crossref_primary_10_30837_ITSSI_2023_24_145
PublicationCentury 2000
PublicationDate 2023-08-05
PublicationDateYYYYMMDD 2023-08-05
PublicationDate_xml – month: 08
  year: 2023
  text: 2023-08-05
  day: 05
PublicationDecade 2020
PublicationTitle Sučasnij stan naukovih doslìdženʹ ta tehnologìj v promislovostì (Online)
PublicationYear 2023
SSID ssj0002876021
ssib044762074
ssib036251356
Score 2.2271311
Snippet SLAM (Simultaneous Localization and Mapping) is a relevant topic of research and development in the field of robotics and computer vision. SLAM finds wide...
SourceID crossref
SourceType Index Database
StartPage 145
Title METHOD OF SIMULTANEOUS LOCALIZATION AND MAPPING FOR CONSTRUCTION OF 2.5D MAPS OF THE ENVIRONMENT USING ROS
hasFullText 1
inHoldings 1
isFullTextHit
isPrint
journalDatabaseRights – providerCode: PRVAON
  databaseName: DOAJ Directory of Open Access Journals
  customDbUrl:
  eissn: 2524-2296
  dateEnd: 99991231
  omitProxy: false
  ssIdentifier: ssj0002876021
  issn: 2522-9818
  databaseCode: DOA
  dateStart: 20170101
  isFulltext: true
  titleUrlDefault: https://www.doaj.org/
  providerName: Directory of Open Access Journals
– providerCode: PRVHPJ
  databaseName: ROAD: Directory of Open Access Scholarly Resources
  customDbUrl:
  eissn: 2524-2296
  dateEnd: 99991231
  omitProxy: false
  ssIdentifier: ssib044762074
  issn: 2522-9818
  databaseCode: M~E
  dateStart: 20170101
  isFulltext: true
  titleUrlDefault: https://road.issn.org
  providerName: ISSN International Centre
link http://cvtisr.summon.serialssolutions.com/2.0.0/link/0/eLvHCXMwtV1Lb5tAEF65aVX1UvWpvsWhPiFcdgEDR-I4iVUbKoOrqBcLWEjsWBAlNkr_d39AZ3aBIFeVmkMvlr3srtfM59nZYeYbQj6DDTDUEyvWdM65ZqZYyD1zEvhf5bFjMjPOE8EzO7V93zk7c7_1er-aXJhqYxeFc3vrXv1XUUMbCBtTZ-8h7nZSaID3IHR4BbHD6z8JfjaOToMjjOYJJ7PFNPL8cbAI1Wkw8qaTH7LKDnJKzTw80p-ocAxUR4EfRvOFCCjBkWxgiQ5hExQ09r9P5oGPzP8qVuo4UedB2DVsw50wS4_im2K1Fg4KtYh3l2W1ulB5iSas0fdGvD-y-odjUHUjr3_oqttY3WbStS87rNUKQ8YAfJuywnwU0brPiVq7r6vNzx0vK6Hmzss2ytjHkdlGXgBdeL5qHxuEu8sLLA8jLn2VpnHDPV67PpghAu-sOw3JwHjUXKdW4FnTZmqMyTK5NXgZLpOZzRKlqqaSxrLe9amsarC_oRhgoeIz7UkEe9sA1zBg5qAd2mXv3ttV21hHOGWJWZZijiXOsWQmHLmsB-Qhsy3X6TgCQAuCRWHRDmmgacJ-1TAWrYU71B7qIqGw_f0yG0x8zZc_ltqxuDqmU_SMPK3PPIonsfqc9LLiBXncpFy8JGsJWSU4VrqQVbqQVQCySg1ZBSCrdCGLIxGy2CHEDwBZpQNZRUBWAci-IuHxOBqdanUNEC2Fk7TmuEh-lFOaJpnuZlnsGDnXhzG3kjQ2KO5OjOopTRxqczfROY0ZR85D6nLq5MZrclCURfaGKLZh5oaFhdrSxExs10UiQYfCnc64k9jmW6I2d2l5JYleln8X3bt79X5PntzB9wM52F7vso_kUVptVzfXn4T0fwOwHYUh
linkProvider Directory of Open Access Journals
openUrl ctx_ver=Z39.88-2004&ctx_enc=info%3Aofi%2Fenc%3AUTF-8&rfr_id=info%3Asid%2Fsummon.serialssolutions.com&rft_val_fmt=info%3Aofi%2Ffmt%3Akev%3Amtx%3Ajournal&rft.genre=article&rft.atitle=METHOD+OF+SIMULTANEOUS+LOCALIZATION+AND+MAPPING+FOR+CONSTRUCTION+OF+2.5D+MAPS+OF+THE+ENVIRONMENT+USING+ROS&rft.jtitle=Su%C4%8Dasnij+stan+naukovih+dosl%C3%ACd%C5%BEen%CA%B9+ta+tehnolog%C3%ACj+v+promislovost%C3%AC+%28Online%29&rft.au=Nevlyudov%2C+Igor&rft.au=Novoselov%2C+Sergiy&rft.au=Sukhachov%2C+Konstantin&rft.date=2023-08-05&rft.issn=2522-9818&rft.eissn=2524-2296&rft.issue=2+%2824%29&rft.spage=145&rft.epage=160&rft_id=info:doi/10.30837%2FITSSI.2023.24.145&rft.externalDBID=n%2Fa&rft.externalDocID=10_30837_ITSSI_2023_24_145
thumbnail_l http://covers-cdn.summon.serialssolutions.com/index.aspx?isbn=/lc.gif&issn=2522-9818&client=summon
thumbnail_m http://covers-cdn.summon.serialssolutions.com/index.aspx?isbn=/mc.gif&issn=2522-9818&client=summon
thumbnail_s http://covers-cdn.summon.serialssolutions.com/index.aspx?isbn=/sc.gif&issn=2522-9818&client=summon