Change search
CiteExportLink to record
Permanent link

Direct link
Cite
Citation style
  • apa
  • 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
Enhancing Visual Perception of Shape through Tactile Glances
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.ORCID iD: 0000-0003-0579-3372
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. 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.ORCID iD: 0000-0003-2965-2953
2013 (English)In: Intelligent Robots and Systems (IROS), 2013 IEEE/RSJ International Conference on, IEEE conference proceedings, 2013, 3180-3186 p.Conference paper, Published paper (Refereed)
Abstract [en]

Object shape information is an important parameter in robot grasping tasks. However, it may be difficult to obtain accurate models of novel objects due to incomplete and noisy sensory measurements. In addition, object shape may change due to frequent interaction with the object (cereal boxes, etc). In this paper, we present a probabilistic approach for learning object models based on visual and tactile perception through physical interaction with an object. Our robot explores unknown objects by touching them strategically at parts that are uncertain in terms of shape. The robot starts by using only visual features to form an initial hypothesis about the object shape, then gradually adds tactile measurements to refine the object model. Our experiments involve ten objects of varying shapes and sizes in a real setup. The results show that our method is capable of choosing a small number of touches to construct object models similar to real object shapes and to determine similarities among acquired models.

Place, publisher, year, edition, pages
IEEE conference proceedings, 2013. 3180-3186 p.
Series
IEEE International Conference on Intelligent Robots and Systems, ISSN 2153-0858
Keyword [en]
Initial hypothesis, Learning object model, Physical interactions, Probabilistic approaches, Sensory measurement, Tactile perception, Unknown objects, Visual perception
National Category
Computer Vision and Robotics (Autonomous Systems)
Identifiers
URN: urn:nbn:se:kth:diva-133212DOI: 10.1109/IROS.2013.6696808ISI: 000331367403037Scopus ID: 2-s2.0-84891043014ISBN: 978-1-4673-6358-7 (print)OAI: oai:DiVA.org:kth-133212DiVA: diva2:659977
Conference
2013 26th IEEE/RSJ International Conference on Intelligent Robots and Systems: New Horizon, IROS 2013; Tokyo; Japan; 3 November 2013 through 8 November 2013
Note

QC 20131104

Available from: 2013-10-28 Created: 2013-10-28 Last updated: 2014-04-10Bibliographically approved

Open Access in DiVA

2013_IROS_bbhk.pdf(5773 kB)210 downloads
File information
File name FULLTEXT01.pdfFile size 5773 kBChecksum SHA-512
e2b4e73647754364a0eaf51a77c636c45011074c3659d75c86dfe6ba90bdeb44d12c28c20fbd6416134777f1db9c80508c8b3901c90770fd5eef0122f229d1db
Type fulltextMimetype application/pdf

Other links

Publisher's full textScopusiros2013

Search in DiVA

By author/editor
Björkman, MårtenBekiroglu, YaseminHögman, VirgileKragic, Danica
By organisation
Computer Vision and Active Perception, CVAPCentre for Autonomous Systems, CAS
Computer Vision and Robotics (Autonomous Systems)

Search outside of DiVA

GoogleGoogle Scholar
Total: 210 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

doi
isbn
urn-nbn

Altmetric score

doi
isbn
urn-nbn
Total: 416 hits
CiteExportLink to record
Permanent link

Direct link
Cite
Citation style
  • apa
  • 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