liu.seSearch for publications in DiVA
Change search
CiteExportLink to record
Permanent link

Direct link
Cite
Citation style
  • apa
  • harvard1
  • ieee
  • modern-language-association-8th-edition
  • vancouver
  • oxford
  • 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
Methods for vision-based robotic automation
Linköping University, Department of Electrical Engineering, Computer Vision. Linköping University, The Institute of Technology.
2005 (English)Licentiate thesis, monograph (Other academic)
Abstract [en]

This thesis presents work done within the EC-founded project VISATEC. Due to the different directions of the VISATEC project this thesis has a few different threads.

A novel presentation scheme for medium level vision features applied to range sensor data and to image sequences. Some estimation procedures for this representation have been implemented and tested. The representation is tensor based and uses higher order tensors in a projective space. The tensor can hold information on several local structures including their relative position and orientation. This information can also be extracted from the tensor.

A number of well-known techniques are combined in a novel way to be able to perform object pose estimation under changes of the object in position, scale and rotation from a single 2D image. The local feature used is a patch which is resampled in a log-polar pattern. A number of local features are matched to a database and the k nearest neighbors vote an object state parameters. This most probable object states are found through mean-shift clustering.

A system using multi-cue integration as a means of reaching a higher level of system-level robustness and a higher lever of accuracy is developed and evaluated in an industrial-like-setting. The system is based around a robotic manipulator arm with an attached camera. The system is designed to solve parts of the bin-picking problem. The above mentioned 2D technique for object pose estimation is also evaluated within this system.

Place, publisher, year, edition, pages
Institutionen för systemteknik , 2005. , 109 p.
Series
Linköping Studies in Science and Technology. Thesis, ISSN 0280-7971 ; 1161
Keyword [en]
VISATEC, robotic, camera, 2D technique, image sequences
National Category
Engineering and Technology
Identifiers
URN: urn:nbn:se:liu:diva-5665Local ID: LiU-TEC-LIC-2005:16ISBN: 91-85299-37-5 (print)OAI: oai:DiVA.org:liu-5665DiVA: diva2:21426
Presentation
(English)
Available from: 2005-04-29 Created: 2005-04-29 Last updated: 2010-04-23

Open Access in DiVA

fulltext(4036 kB)826 downloads
File information
File name FULLTEXT01.pdfFile size 4036 kBChecksum MD5
6dafbe36bd7ddac9f3bd039345f7df898b8806393b6eed44b4258c6cf8ae9293dcff52e1
Type fulltextMimetype application/pdf

Authority records BETA

Viksten, Fredrik

Search in DiVA

By author/editor
Viksten, Fredrik
By organisation
Computer VisionThe Institute of Technology
Engineering and Technology

Search outside of DiVA

GoogleGoogle Scholar
Total: 826 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

isbn
urn-nbn

Altmetric score

isbn
urn-nbn
Total: 1518 hits
CiteExportLink to record
Permanent link

Direct link
Cite
Citation style
  • apa
  • harvard1
  • ieee
  • modern-language-association-8th-edition
  • vancouver
  • oxford
  • 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