Publication detail

General concepts of multi-sensor data-fusion based SLAM

KLEČKA, J. HORÁK, K. BOŠTÍK, O.

Original Title

General concepts of multi-sensor data-fusion based SLAM

English Title

General concepts of multi-sensor data-fusion based SLAM

Type

journal article in Web of Science

Language

en

Original Abstract

This paper is approaching a problem of Simultaneous Localization and Mapping (SLAM) algorithms focused specifically on processing of data from a heterogeneous set of sensors concurrently. Sensors are considered to be different in a sense of measured physical quantity and so the problem of effective data-fusion is discussed. A special extension of the standard probabilistic approach to SLAM algorithms is presented. This extension is composed of two parts. Firstly is presented general perspective multiple-sensors based SLAM and then thee archetypical special cases are discuses. One archetype provisionally designated as ”partially collective mapping” has been analyzed also in a practical perspective because it implies a promising options for implicit map-level data-fusion.

English abstract

This paper is approaching a problem of Simultaneous Localization and Mapping (SLAM) algorithms focused specifically on processing of data from a heterogeneous set of sensors concurrently. Sensors are considered to be different in a sense of measured physical quantity and so the problem of effective data-fusion is discussed. A special extension of the standard probabilistic approach to SLAM algorithms is presented. This extension is composed of two parts. Firstly is presented general perspective multiple-sensors based SLAM and then thee archetypical special cases are discuses. One archetype provisionally designated as ”partially collective mapping” has been analyzed also in a practical perspective because it implies a promising options for implicit map-level data-fusion.

Keywords

Simultaneous localization and mapping (SLAM);Localization;Mapping;Data fusion;Partially collective mapping

Released

01.06.2020

Publisher

Institute of Advanced Engineering and Science

ISBN

2089-4856

Periodical

International Journal of Robotics and Automation (IJRA)

Year of study

9

Number

2

State

ID

Pages from

63

Pages to

72

Pages count

10

URL

http://ijra.iaescore.com/index.php/IJRA/article/view/20258/12906

Full text in the Digital Library

http://hdl.handle.net/11012/193374

Documents

BibTex 


@article{BUT164281,
  author="Jan {Klečka} and Karel {Horák} and Ondřej {Boštík}",
  title="General concepts of multi-sensor data-fusion based SLAM",
  annote="This paper is approaching a problem of Simultaneous Localization and Mapping (SLAM) algorithms focused specifically on processing of data from a heterogeneous set of sensors concurrently. Sensors are considered to be different in a sense of measured physical quantity and so the problem of effective data-fusion is discussed. A
special extension of the standard probabilistic approach to SLAM algorithms is presented. This extension is composed of two parts. Firstly is presented general perspective multiple-sensors based SLAM and then thee archetypical special cases are discuses. One archetype provisionally designated as ”partially collective mapping” has been analyzed also in a practical perspective because it implies a promising options for implicit map-level data-fusion.",
  address="Institute of Advanced Engineering and Science",
  chapter="164281",
  doi="10.11591/ijra.v9i2.pp63-72",
  howpublished="online",
  institution="Institute of Advanced Engineering and Science",
  number="2",
  volume="9",
  year="2020",
  month="june",
  pages="63--72",
  publisher="Institute of Advanced Engineering and Science",
  type="journal article in Web of Science"
}