Publication detail

Non odometry SLAM and Effect of Feature Space Parametrization on its Covariance Convergence

KLEČKA, J. HORÁK, K. DAVÍDEK, D. NOVÁČEK, P.

Original Title

Non odometry SLAM and Effect of Feature Space Parametrization on its Covariance Convergence

English Title

Non odometry SLAM and Effect of Feature Space Parametrization on its Covariance Convergence

Type

conference paper

Language

en

Original Abstract

This paper is aimed at non-odometry feature-based variant of SLAM (Simultaneous Localisation and Mapping) algorithm. The main focus has been given to processing of linearly constraint map landmarks observations. The observation model was simplified to linear and with this assumption is given derivation of three different variants of applicable SLAM algorithm – first variant which doesn’t take into consideration any map feature constraints, second variant which optimally process data under linear constraints assumption and third reduced variant which is designed to slightly suboptimal processing with significantly lower computational complexity. The performance of described methods was tested on synthetic data and results of simulations are presented at the end of this paper.

English abstract

This paper is aimed at non-odometry feature-based variant of SLAM (Simultaneous Localisation and Mapping) algorithm. The main focus has been given to processing of linearly constraint map landmarks observations. The observation model was simplified to linear and with this assumption is given derivation of three different variants of applicable SLAM algorithm – first variant which doesn’t take into consideration any map feature constraints, second variant which optimally process data under linear constraints assumption and third reduced variant which is designed to slightly suboptimal processing with significantly lower computational complexity. The performance of described methods was tested on synthetic data and results of simulations are presented at the end of this paper.

Keywords

SLAM, non-odometry SLAM, feature-based SLAM, Simultaneous Localisation and Mapping, mapping, parametrization of feature space

Released

06.10.2016

ISBN

2405-8963

Periodical

IFAC-PapersOnLine (ELSEVIER)

Year of study

2016

Number

14

State

NL

Pages from

357

Pages to

362

Pages count

6

Documents

BibTex


@inproceedings{BUT128843,
  author="Jan {Klečka} and Karel {Horák} and Daniel {Davídek} and Petr {Nováček}",
  title="Non odometry SLAM and Effect of Feature Space Parametrization on its Covariance Convergence",
  annote="This paper is aimed at non-odometry feature-based variant of SLAM (Simultaneous Localisation and Mapping) algorithm. The main focus has been given to processing of linearly constraint map landmarks observations. The observation model was simplified to linear and with this assumption is given derivation of three different variants of applicable SLAM algorithm – first variant which doesn’t take into consideration any map feature constraints, second variant which optimally process data under linear constraints assumption and third reduced variant which is designed to slightly suboptimal processing with significantly lower computational complexity. The performance of described methods was tested on synthetic data and results of simulations are presented at the end of this paper.",
  booktitle="14th IFAC Conference on Programmable Devices and Embedded Systems - PDeS 2016",
  chapter="128843",
  doi="10.1016/j.ifacol.2016.12.024",
  howpublished="electronic, physical medium",
  number="14",
  year="2016",
  month="october",
  pages="357--362",
  type="conference paper"
}