Robust Approaches for Localization on Multi-camera Systems in Dynamic Environments

Marco Sewtz, Xiaozhou Luo, Johannes Landgraf, Tim Bodenmuller, Rudolph Triebel

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

13 Scopus citations

Abstract

Localization of humanoid robots in real-life scenarios has to robustly tackle dynamic environments and provide coherent data and tight integration for follow-up tasks. However state-of-the-art solutions, like ORBSlam2 [1], lack this ability. In this work we present two adaptations of ORBSlam2 for a multi-camera setup on the DLR Rollin' Justin System, one distributed multi-slam and one combined single-process system. Further, we introduce the usage of pre-recorded maps with ORBSlam2 and the alignment with semantic maps for planning. We compare performance of the adaptations against and the original approach in realistic experiments and discuss advantages and disadvantages of all methods.

Original languageEnglish
Title of host publication2021 International Conference on Automation, Robotics and Applications, ICARA 2021
PublisherInstitute of Electrical and Electronics Engineers Inc.
Pages211-215
Number of pages5
ISBN (Electronic)9780738142906
DOIs
StatePublished - 4 Feb 2021
Event2021 International Conference on Automation, Robotics and Applications, ICARA 2021 - Virtual, Prague, Czech Republic
Duration: 4 Feb 20216 Feb 2021

Publication series

Name2021 International Conference on Automation, Robotics and Applications, ICARA 2021

Conference

Conference2021 International Conference on Automation, Robotics and Applications, ICARA 2021
Country/TerritoryCzech Republic
CityVirtual, Prague
Period4/02/216/02/21

Keywords

  • ORBSlam
  • SLAM
  • dynamic environments
  • localization
  • mapping
  • multi-camera SLAM

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