his.sePublications
Change search
CiteExportLink to record
Permanent link

Direct link
Cite
Citation style
  • apa
  • harvard1
  • 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
Row-detection on an agricultural field using omnidirectional camera
University of Skövde, School of Technology and Society.
School of Information Science, Computer and Electrical Engineering, Halmstad University, Halmstad, Sweden.
2010 (English)In: The IEEE/RSJ 2010 International Conference on Intelligent Robots and Systems (IROS 2010): Conference Proceedings, IEEE conference proceedings, 2010, 4982-4987 p.Conference paper, (Refereed)
Abstract [en]

This paper describes a method of detecting parallel  rows  on  an  agricultural  field  using  an  omnidirectional camera.  The  method  works  both  on  cameras  with  a  fisheye lens and cameras with a catadioptric lens. A combination of an edge based method and a Hough transform method is suggested to find the rows. The vanishing point of several parallel rows is estimated using a second Hough transform. The method is evaluated on synthetic images generated with calibration data from real lenses. Scenes with several rows are produced, where each  plant  is  positioned  with  a  specified  error.  Experiments are  performed  on  these  synthetic  images  and  on  real  field images. The result shows that good accuracy is obtained on the vanishing point once it is detected correctly. Further it shows that the edge based method works best when the rows consists of solid lines, and the Hough method works best when the rows consists  of  individual  plants.  The  experiments  also  show  that the combined method provides better detection than using the methods separately.

Place, publisher, year, edition, pages
IEEE conference proceedings, 2010. 4982-4987 p.
Series
IEEE International Conference on Intelligent Robots and Systems. Proceedings, ISSN 2153-0858
National Category
Engineering and Technology
Research subject
Technology
Identifiers
URN: urn:nbn:se:his:diva-4597DOI: 10.1109/IROS.2010.5650964ISI: 000287672004089Scopus ID: 2-s2.0-78651477189ISBN: 978-1-4244-6676-4 (print)ISBN: 978-1-4244-6675-7 (print)ISBN: 978-1-4244-6674-0 (print)OAI: oai:DiVA.org:his-4597DiVA: diva2:389808
Conference
23rd IEEE/RSJ 2010 International Conference on Intelligent Robots and Systems, IROS 2010; Taipei; 18 October 2010 through 22 October 2010
Available from: 2011-01-20 Created: 2011-01-20 Last updated: 2017-02-28Bibliographically approved
In thesis
1. Vision-Based Perception for Localization of Autonomous Agricultural Robots
Open this publication in new window or tab >>Vision-Based Perception for Localization of Autonomous Agricultural Robots
2017 (English)Doctoral thesis, comprehensive summary (Other academic)
Abstract [en]

In this thesis Stefan investigates how cameras can be used for localization of an agricultural mobile robot. He focuses on relative measurement that can be used to determine where a weeding tool is operating relative a weed detection sensor. It incorporates downward-facing perspective cameras, forward-facing perspective cameras and omnidirectional cameras. Stefan shows how the camera’s ego-motion can be estimated to obtain not only the position in 3D but also the orientation. He also shows how line structures in the field can be used to navigate a robot along the rows.

Place, publisher, year, edition, pages
Skövde: University of Skövde, 2017. 164 p.
Series
Dissertation Series, 16 (2017)
National Category
Robotics
Identifiers
urn:nbn:se:his:diva-13408 (URN)978-91-982690-7-9 (ISBN)
Opponent
Supervisors
Available from: 2017-02-28 Created: 2017-02-28 Last updated: 2017-03-06Bibliographically approved

Open Access in DiVA

No full text

Other links

Publisher's full textScopus

Search in DiVA

By author/editor
Ericson, Stefan
By organisation
School of Technology and Society
Engineering and Technology

Search outside of DiVA

GoogleGoogle Scholar

Altmetric score

Total: 739 hits
CiteExportLink to record
Permanent link

Direct link
Cite
Citation style
  • apa
  • harvard1
  • 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