Publication detail

VISUAL SLAM BASED ON PHASE CORRELATION AND PARTICLE FILTERS

RŮŽIČKA, M. MAŠEK, P.

Original Title

VISUAL SLAM BASED ON PHASE CORRELATION AND PARTICLE FILTERS

Type

conference paper

Language

English

Original Abstract

This paper deals with design of visual SLAM method, which is based on phase correlation and particle filters. This method can be used for localization of autonomous mobile robots inside of buildings. The method contains two parts. The first one is mapping of environ-ment, where the mobile robot operates. For this purpose was used phase correlation and images stitching method. The second one is localization problem, which was solved by particle filters, where a particles weights re-sampling was realized by phase correlation image processing method as well. Localization uses the map, which was created by phase correlation and stitching method.

Keywords

Phase correlation, particle filters, visual SLAM, localization, mapping, stitching, computer vision, image processing, mobile robot, discrete Fourier transform, inverse discrete Fourier transform and Hanning window.

Authors

RŮŽIČKA, M.; MAŠEK, P.

RIV year

2015

Released

23. 6. 2015

Publisher

Springer

Location

Switzerland

ISBN

978-3-319-19823-1

Book

MENDEL 2015, Recent Advances in Soft Computing

Edition

Advances in Inteligent Systems and Computing

Edition number

378

ISBN

2194-5357

Periodical

Advances in Intelligent Systems and Computing

Year of study

378

State

Swiss Confederation

Pages from

353

Pages to

362

Pages count

10

BibTex

@inproceedings{BUT115145,
  author="Michal {Růžička} and Petr {Mašek}",
  title="VISUAL SLAM BASED ON PHASE CORRELATION AND PARTICLE FILTERS",
  booktitle="MENDEL 2015, Recent Advances in Soft Computing",
  year="2015",
  series="Advances in Inteligent Systems and Computing",
  journal="Advances in Intelligent Systems and Computing",
  volume="378",
  number="378",
  pages="353--362",
  publisher="Springer",
  address="Switzerland",
  doi="10.1007/978-3-319-19824-8",
  isbn="978-3-319-19823-1",
  issn="2194-5357"
}