hh.sePublications
Change search
CiteExportLink to record
Permanent link

Direct link
Cite
Citation style
  • apa
  • ieee
  • modern-language-association-8th-edition
  • vancouver
  • Other style
More styles
Language
  • de-DE
  • en-GB
  • en-US
  • fi-FI
  • nn-NO
  • nn-NB
  • sv-SE
  • Other locale
More languages
Output format
  • html
  • text
  • asciidoc
  • rtf
Analysis of two visual odometry systems for use in an agricultural field environment
University of Skövde, Skövde, Sweden.
Halmstad University, School of Information Technology, Halmstad Embedded and Intelligent Systems Research (EIS), CAISR - Center for Applied Intelligent Systems Research.
2018 (English)In: Biosystems Engineering, ISSN 1537-5110, E-ISSN 1537-5129, Vol. 166, p. 116-125Article in journal (Refereed) Published
Abstract [en]

This paper analyses two visual odometry systems for use in an agricultural field environment. The impact of various design parameters and camera setups are evaluated in a simulation environment. Four real field experiments were conducted using a mobile robot operating in an agricultural field. The robot was controlled to travel in a regular back-and-forth pattern with headland turns. The experimental runs were 1.8–3.1 km long and consisted of 32–63,000 frames. The results indicate that a camera angle of 75° gives the best results with the least error. An increased camera resolution only improves the result slightly. The algorithm must be able to reduce error accumulation by adapting the frame rate to minimise error. The results also illustrate the difficulties of estimating roll and pitch using a downward-facing camera. The best results for full 6-DOF position estimation were obtained on a 1.8-km run using 6680 frames captured from the forward-facing cameras. The translation error (x, y, z) is 3.76% and the rotational error (i.e., roll, pitch, and yaw) is 0.0482 deg m−1. The main contributions of this paper are an analysis of design option impacts on visual odometry results and a comparison of two state-of-the-art visual odometry algorithms, applied to agricultural field data. © 2017 IAgrE

Place, publisher, year, edition, pages
London: Academic Press, 2018. Vol. 166, p. 116-125
Keywords [en]
Visual odometry, Agricultural field robots, Visual navigation
National Category
Signal Processing Robotics and automation
Identifiers
URN: urn:nbn:se:hh:diva-35853DOI: 10.1016/j.biosystemseng.2017.11.009ISI: 000424726400009Scopus ID: 2-s2.0-85037985130OAI: oai:DiVA.org:hh-35853DiVA, id: diva2:1166228
Available from: 2017-12-14 Created: 2017-12-14 Last updated: 2025-02-05Bibliographically approved

Open Access in DiVA

fulltext(3938 kB)489 downloads
File information
File name FULLTEXT01.pdfFile size 3938 kBChecksum SHA-512
bce2c58268e4ab9570b37708567d3901fcb091de584d3d5f10871224c3b5131c6c8390f2f59b3bf40b6e5cffd74583a9ad104f861d938c6b24ec88acad9f0479
Type fulltextMimetype application/pdf

Other links

Publisher's full textScopus

Authority records

Åstrand, Björn

Search in DiVA

By author/editor
Åstrand, Björn
By organisation
CAISR - Center for Applied Intelligent Systems Research
In the same journal
Biosystems Engineering
Signal ProcessingRobotics and automation

Search outside of DiVA

GoogleGoogle Scholar
Total: 489 downloads
The number of downloads is the sum of all downloads of full texts. It may include eg previous versions that are now no longer available

doi
urn-nbn

Altmetric score

doi
urn-nbn
Total: 636 hits
CiteExportLink to record
Permanent link

Direct link
Cite
Citation style
  • apa
  • ieee
  • modern-language-association-8th-edition
  • vancouver
  • Other style
More styles
Language
  • de-DE
  • en-GB
  • en-US
  • fi-FI
  • nn-NO
  • nn-NB
  • sv-SE
  • Other locale
More languages
Output format
  • html
  • text
  • asciidoc
  • rtf