A Modification of ORB-SLAM2 for Multi-Robot SLAM

Jiabin Chen*, Feipeng Zhao, Junyu Liang

*Corresponding author for this work

Research output: Chapter in Book/Report/Conference proceedingConference contributionpeer-review

Abstract

ORB-SLAM2 consumes much time on descriptors calculating, which is a great challenge for real-time performance of SLAM. In this paper, we proposed a modified ORB-SLAM2 method named SD-SLAM2, which achieved better real-time performance than ORB-SLAM2, by replacing the extraction and description of ORB features with sparse direct method. Based on SD-SLAM2, we implemented centralized collaborative SLAM for multi-robot. Experimental results on popular public datasets demonstrate the performance of SD-SLAM2 in monomer SLAM. We also conducted field experiments for multi-robot, whose results demonstrate the performance of SD-SLAM2 in multi-robot SLAM.

Original languageEnglish
Title of host publicationProceedings of the 35th Chinese Control and Decision Conference, CCDC 2023
PublisherInstitute of Electrical and Electronics Engineers Inc.
Pages2348-2353
Number of pages6
ISBN (Electronic)9798350334722
DOIs
Publication statusPublished - 2023
Event35th Chinese Control and Decision Conference, CCDC 2023 - Yichang, China
Duration: 20 May 202322 May 2023

Publication series

NameProceedings of the 35th Chinese Control and Decision Conference, CCDC 2023

Conference

Conference35th Chinese Control and Decision Conference, CCDC 2023
Country/TerritoryChina
CityYichang
Period20/05/2322/05/23

Keywords

  • ORB-SLAM2
  • SD-SLAM2
  • multi-agent
  • real-time performance
  • sparse direct
  • visual SLAM

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