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
"Robot, bring me something to drink from": object representation for transferring task specific grasps
KTH, School of Computer Science and Communication (CSC), Computer Vision and Active Perception, CVAP.
KTH, School of Computer Science and Communication (CSC), Computer Vision and Active Perception, CVAP.
KTH, School of Computer Science and Communication (CSC), Computer Vision and Active Perception, CVAP.
KTH, School of Computer Science and Communication (CSC), Computer Vision and Active Perception, CVAP.ORCID iD: 0000-0003-2965-2953
2013 (English)In: In IEEE International Conference on Robotics and Automation (ICRA 2012), Workshop on Semantic Perception, Mapping and Exploration (SPME),  St. Paul, MN, USA, May 13, 2012, 2013Conference paper, Published paper (Refereed)
Abstract [en]

In this paper, we present an approach for taskspecificobject representation which facilitates transfer of graspknowledge from a known object to a novel one. Our representation encompasses: (a) several visual object properties,(b) object functionality and (c) task constrains in order to provide a suitable goal-directed grasp. We compare various features describing complementary object attributes to evaluate the balance between the discrimination and generalization properties of the representation. The experimental setup is a scene containing multiple objects. Individual object hypotheses are first detected, categorized and then used as the input to a grasp reasoning system that encodes the task information. Our approach not only allows to find objects in a real world scene that afford a desired task, but also to generate and successfully transfer task-based grasp within and across object categories.

Place, publisher, year, edition, pages
2013.
Keyword [en]
computer vision, robotics, object recognition, grasping
National Category
Robotics Computer Vision and Robotics (Autonomous Systems)
Identifiers
URN: urn:nbn:se:kth:diva-136376OAI: oai:DiVA.org:kth-136376DiVA: diva2:675934
Conference
IEEE International Conference on Robotics and Automation (ICRA 2012), Workshop on Semantic Perception, Mapping and Exploration (SPME)
Funder
EU, FP7, Seventh Framework Programme, IST-FP7-IP-215821Swedish Foundation for Strategic Research
Note

QC 20140317

Available from: 2013-12-04 Created: 2013-12-04 Last updated: 2014-03-17Bibliographically approved

Open Access in DiVA

No full text

Authority records BETA

Kragic, Danica

Search in DiVA

By author/editor
Madry, MariannaSong, DanEk, Carl HenrikKragic, Danica
By organisation
Computer Vision and Active Perception, CVAP
RoboticsComputer Vision and Robotics (Autonomous Systems)

Search outside of DiVA

GoogleGoogle Scholar

urn-nbn

Altmetric score

urn-nbn
Total: 60 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