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Enabling grasping of unknown objects through a synergistic use of edge and surface information
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.
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2012 (English)In: The international journal of robotics research, ISSN 0278-3649, E-ISSN 1741-3176, Vol. 31, no 10, p. 1190-1213Article in journal (Refereed) Published
Abstract [en]

Grasping unknown objects based on visual input, where no a priori knowledge about the objects is used, is a challenging problem. In this paper, we present an Early Cognitive Vision system that builds a hierarchical representation based on edge and texture information which provides a sparse but powerful description of the scene. Based on this representation, we generate contour-based and surface-based grasps. We test our method in two real-world scenarios, as well as on a vision-based grasping benchmark providing a hybrid scenario using real-world stereo images as input and a simulator for extensive and repetitive evaluation of the grasps. The results show that the proposed method is able to generate successful grasps, and in particular that the contour and surface information are complementary for the task of grasping unknown objects. This allows for dealing with rather complex scenes.

Place, publisher, year, edition, pages
2012. Vol. 31, no 10, p. 1190-1213
Keywords [en]
vision-based grasping, grasping unknown objects, visual scene representation, dexterous hands
National Category
Computer Vision and Robotics (Autonomous Systems)
Identifiers
URN: urn:nbn:se:kth:diva-103144DOI: 10.1177/0278364912452621ISI: 000307838700005Scopus ID: 2-s2.0-84865526912OAI: oai:DiVA.org:kth-103144DiVA, id: diva2:559394
Funder
EU, European Research Council, FP7-ICT-270273 FP7-IST-270212ICT - The Next Generation
Note

QC 20121009

Available from: 2012-10-09 Created: 2012-10-04 Last updated: 2018-01-12Bibliographically approved

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Kragic, Danica

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Computer Vision and Active Perception, CVAPCentre for Autonomous Systems, CAS
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CiteExportLink to record
Permanent link

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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