Multiple hypotheses data association propagation for robust monocular-based SLAM algorithms

M. Soto-Alvarez, Petri Honkamaa

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

3 Citations (Scopus)

Abstract

Data Association is probably the most important step of every monocular Simultaneous Localization and Mapping (SLAM) algorithm because it provides the basic information to the estimation module, independently on the estimation algorithm of choice. Although important, it is also a difficult task because the analytic solution is NP-Hard. The usual approximation is obtaining only one data association hypothesis per frame which affects the robustness of the result [1][2][3][4][5]. In this paper, a data association approach is presented, where multiple hypotheses are propagated between frames using a probabilistic framework. Experimental results, using real and synthetic data, show that the proposed algorithm produces promising results with respect to other state of the art methods.
Original languageEnglish
Title of host publicationProceedings
Subtitle of host publicationIEEE International Conference on Acoustics, Speech and Signal Processing, ICASSP 2014
PublisherInstitute of Electrical and Electronic Engineers IEEE
Pages6543-6547
ISBN (Electronic)978-1-4799-2893-4
ISBN (Print)978-147992892-7
DOIs
Publication statusPublished - 2014
MoE publication typeA4 Article in a conference publication
EventIEEE International Conference on Acoustics, Speech, and Signal Processing, ICASSP 2014 - Florence, Italy
Duration: 4 May 20149 May 2014

Conference

ConferenceIEEE International Conference on Acoustics, Speech, and Signal Processing, ICASSP 2014
Abbreviated titleICASSP 2014
CountryItaly
CityFlorence
Period4/05/149/05/14

Keywords

  • algorithms
  • localisation
  • mapping
  • data association

Cite this

Soto-Alvarez, M., & Honkamaa, P. (2014). Multiple hypotheses data association propagation for robust monocular-based SLAM algorithms. In Proceedings: IEEE International Conference on Acoustics, Speech and Signal Processing, ICASSP 2014 (pp. 6543-6547). Institute of Electrical and Electronic Engineers IEEE. https://doi.org/10.1109/ICASSP.2014.6854865
Soto-Alvarez, M. ; Honkamaa, Petri. / Multiple hypotheses data association propagation for robust monocular-based SLAM algorithms. Proceedings: IEEE International Conference on Acoustics, Speech and Signal Processing, ICASSP 2014. Institute of Electrical and Electronic Engineers IEEE, 2014. pp. 6543-6547
@inproceedings{ae80026eba494628930f6c89c8b85153,
title = "Multiple hypotheses data association propagation for robust monocular-based SLAM algorithms",
abstract = "Data Association is probably the most important step of every monocular Simultaneous Localization and Mapping (SLAM) algorithm because it provides the basic information to the estimation module, independently on the estimation algorithm of choice. Although important, it is also a difficult task because the analytic solution is NP-Hard. The usual approximation is obtaining only one data association hypothesis per frame which affects the robustness of the result [1][2][3][4][5]. In this paper, a data association approach is presented, where multiple hypotheses are propagated between frames using a probabilistic framework. Experimental results, using real and synthetic data, show that the proposed algorithm produces promising results with respect to other state of the art methods.",
keywords = "algorithms, localisation, mapping, data association",
author = "M. Soto-Alvarez and Petri Honkamaa",
year = "2014",
doi = "10.1109/ICASSP.2014.6854865",
language = "English",
isbn = "978-147992892-7",
pages = "6543--6547",
booktitle = "Proceedings",
publisher = "Institute of Electrical and Electronic Engineers IEEE",
address = "United States",

}

Soto-Alvarez, M & Honkamaa, P 2014, Multiple hypotheses data association propagation for robust monocular-based SLAM algorithms. in Proceedings: IEEE International Conference on Acoustics, Speech and Signal Processing, ICASSP 2014. Institute of Electrical and Electronic Engineers IEEE, pp. 6543-6547, IEEE International Conference on Acoustics, Speech, and Signal Processing, ICASSP 2014, Florence, Italy, 4/05/14. https://doi.org/10.1109/ICASSP.2014.6854865

Multiple hypotheses data association propagation for robust monocular-based SLAM algorithms. / Soto-Alvarez, M.; Honkamaa, Petri.

Proceedings: IEEE International Conference on Acoustics, Speech and Signal Processing, ICASSP 2014. Institute of Electrical and Electronic Engineers IEEE, 2014. p. 6543-6547.

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

TY - GEN

T1 - Multiple hypotheses data association propagation for robust monocular-based SLAM algorithms

AU - Soto-Alvarez, M.

AU - Honkamaa, Petri

PY - 2014

Y1 - 2014

N2 - Data Association is probably the most important step of every monocular Simultaneous Localization and Mapping (SLAM) algorithm because it provides the basic information to the estimation module, independently on the estimation algorithm of choice. Although important, it is also a difficult task because the analytic solution is NP-Hard. The usual approximation is obtaining only one data association hypothesis per frame which affects the robustness of the result [1][2][3][4][5]. In this paper, a data association approach is presented, where multiple hypotheses are propagated between frames using a probabilistic framework. Experimental results, using real and synthetic data, show that the proposed algorithm produces promising results with respect to other state of the art methods.

AB - Data Association is probably the most important step of every monocular Simultaneous Localization and Mapping (SLAM) algorithm because it provides the basic information to the estimation module, independently on the estimation algorithm of choice. Although important, it is also a difficult task because the analytic solution is NP-Hard. The usual approximation is obtaining only one data association hypothesis per frame which affects the robustness of the result [1][2][3][4][5]. In this paper, a data association approach is presented, where multiple hypotheses are propagated between frames using a probabilistic framework. Experimental results, using real and synthetic data, show that the proposed algorithm produces promising results with respect to other state of the art methods.

KW - algorithms

KW - localisation

KW - mapping

KW - data association

U2 - 10.1109/ICASSP.2014.6854865

DO - 10.1109/ICASSP.2014.6854865

M3 - Conference article in proceedings

SN - 978-147992892-7

SP - 6543

EP - 6547

BT - Proceedings

PB - Institute of Electrical and Electronic Engineers IEEE

ER -

Soto-Alvarez M, Honkamaa P. Multiple hypotheses data association propagation for robust monocular-based SLAM algorithms. In Proceedings: IEEE International Conference on Acoustics, Speech and Signal Processing, ICASSP 2014. Institute of Electrical and Electronic Engineers IEEE. 2014. p. 6543-6547 https://doi.org/10.1109/ICASSP.2014.6854865