kth.sePublications
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
A database for reproducible manipulation research: CapriDB – Capture, Print, Innovate
KTH, School of Computer Science and Communication (CSC), Robotics, perception and learning, RPL.ORCID iD: 0000-0003-1114-6040
KTH, School of Computer Science and Communication (CSC), Robotics, perception and learning, RPL.ORCID iD: 0000-0003-3731-0582
KTH, School of Computer Science and Communication (CSC), Robotics, perception and learning, RPL.ORCID iD: 0000-0001-5344-8042
Show others and affiliations
2017 (English)In: Data in Brief, ISSN 2352-3409, Vol. 11, p. 491-498Article in journal (Refereed) Published
Abstract [en]

We present a novel approach and database which combines the inexpensive generation of 3D object models via monocular or RGB-D camera images with 3D printing and a state of the art object tracking algorithm. Unlike recent efforts towards the creation of 3D object databases for robotics, our approach does not require expensive and controlled 3D scanning setups and aims to enable anyone with a camera to scan, print and track complex objects for manipulation research. The proposed approach results in detailed textured mesh models whose 3D printed replicas provide close approximations of the originals. A key motivation for utilizing 3D printed objects is the ability to precisely control and vary object properties such as the size, material properties and mass distribution in the 3D printing process to obtain reproducible conditions for robotic manipulation research. We present CapriDB – an extensible database resulting from this approach containing initially 40 textured and 3D printable mesh models together with tracking features to facilitate the adoption of the proposed approach.

Place, publisher, year, edition, pages
Elsevier, 2017. Vol. 11, p. 491-498
National Category
Computer and Information Sciences
Identifiers
URN: urn:nbn:se:kth:diva-210103DOI: 10.1016/j.dib.2017.02.015ISI: 000453174100071PubMedID: 28289699Scopus ID: 2-s2.0-85014438696OAI: oai:DiVA.org:kth-210103DiVA, id: diva2:1118493
Note

QC 20170630

Available from: 2017-06-30 Created: 2017-06-30 Last updated: 2024-08-23Bibliographically approved

Open Access in DiVA

No full text in DiVA

Other links

Publisher's full textPubMedScopus

Authority records

Pokorny, Florian T.Pauwels, KarlButepage, JudithScherer, ClaraKragic, Danica

Search in DiVA

By author/editor
Pokorny, Florian T.Pauwels, KarlButepage, JudithScherer, ClaraKragic, Danica
By organisation
Robotics, perception and learning, RPL
Computer and Information Sciences

Search outside of DiVA

GoogleGoogle Scholar

doi
pubmed
urn-nbn

Altmetric score

doi
pubmed
urn-nbn
Total: 188 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