ROSLAM-A faster algorithm for simultaneous localization and mapping (SLAM)

Research output: Chapter in Book/Report/Conference proceedingConference contribution

1 Citation (Scopus)

Abstract

Computationally efficient SLAM (CESLAM) has been proposed to solve simultaneous localization and mapping problem in real-time design. CESLAM first uses the landmark measurement with the maximum likelihood to update the particle states and then update their associated landmarks later. This improves the accuracy of localization and mapping by avoiding unnecessary comparisons. This paper describes a modified version of CESLAM called rapidly operations SLAM (ROSLAM) which improves the runtime even further. We present an empirical evaluation of ROSLAM in a simulated environment which shows that it speeds up previous well known algorithms by 100 %.

Original languageEnglish
Title of host publicationRobot Intelligence Technology and Applications 4 - Results from the 4th International Conference on Robot Intelligence Technology and Applications
EditorsFakhri Karray, Jong-Hwan Kim, Hyun Myung, Jun Jo, Peter Sincak
PublisherSpringer Verlag
Pages65-74
Number of pages10
ISBN (Print)9783319312910
DOIs
Publication statusPublished - 2017 Jan 1
Event4th International Conference on Robot Intelligence Technology and Applications, RiTA 2015 - Bucheon, Korea, Republic of
Duration: 2015 Dec 142015 Dec 16

Publication series

NameAdvances in Intelligent Systems and Computing
Volume447
ISSN (Print)2194-5357

Other

Other4th International Conference on Robot Intelligence Technology and Applications, RiTA 2015
CountryKorea, Republic of
CityBucheon
Period15/12/1415/12/16

Keywords

  • CESLAM
  • Extended kalman filter
  • FastSLAM
  • Particle filter

ASJC Scopus subject areas

  • Control and Systems Engineering
  • Computer Science(all)

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