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
Learning grasping points with shape context
KTH, School of Computer Science and Communication (CSC), Centres, Centre for Autonomous Systems, CAS. KTH, School of Computer Science and Communication (CSC), Computer Vision and Active Perception, CVAP.
KTH, School of Computer Science and Communication (CSC), Centres, Centre for Autonomous Systems, CAS. KTH, School of Computer Science and Communication (CSC), Computer Vision and Active Perception, CVAP.ORCID iD: 0000-0003-2965-2953
2010 (English)In: Robotics and Autonomous Systems, ISSN 0921-8890, E-ISSN 1872-793X, Vol. 58, no 4, 362-377 p.Article in journal (Refereed) Published
Abstract [en]

This paper presents work on vision based robotic grasping. The proposed method adopts a learning framework where prototypical grasping points are learnt from several examples and then used on novel objects. For representation purposes, we apply the concept of shape context and for learning we use a supervised learning approach in which the classifier is trained with labelled synthetic images. We evaluate and compare the performance of linear and non-linear classifiers. Our results show that a combination of a descriptor based on shape context with a non-linear classification algorithm leads to a stable detection of grasping points for a variety of objects.

Place, publisher, year, edition, pages
2010. Vol. 58, no 4, 362-377 p.
Keyword [en]
Grasping, Shape context, Affordances, SVM
National Category
Computer and Information Science
Identifiers
URN: urn:nbn:se:kth:diva-28268DOI: 10.1016/j.robot.2009.10.003ISI: 000276666100003OAI: oai:DiVA.org:kth-28268DiVA: diva2:387474
Funder
EU, FP7, Seventh Framework Programme, IST-FP7-IP GRASP (2008-2012)
Note
QC 20110114Available from: 2011-01-14 Created: 2011-01-12 Last updated: 2017-12-11Bibliographically approved

Open Access in DiVA

No full text

Other links

Publisher's full text

Authority records BETA

Kragic, Danica

Search in DiVA

By author/editor
Bohg, JeannetteKragic, Danica
By organisation
Centre for Autonomous Systems, CASComputer Vision and Active Perception, CVAP
In the same journal
Robotics and Autonomous Systems
Computer and Information Science

Search outside of DiVA

GoogleGoogle Scholar

doi
urn-nbn

Altmetric score

doi
urn-nbn
Total: 74 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