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
Integrating motion and hierarchical fingertip grasp planning
KTH, School of Computer Science and Communication (CSC), Robotics, perception and learning, RPL. KTH, School of Computer Science and Communication (CSC), Centres, Centre for Autonomous Systems, CAS.
KTH, School of Computer Science and Communication (CSC), Robotics, perception and learning, RPL. KTH, School of Computer Science and Communication (CSC), Centres, Centre for Autonomous Systems, CAS.
KTH, School of Computer Science and Communication (CSC), Robotics, perception and learning, RPL. KTH, School of Computer Science and Communication (CSC), Centres, Centre for Autonomous Systems, CAS.
2017 (English)In: 2017 IEEE International Conference on Robotics and Automation (ICRA), Institute of Electrical and Electronics Engineers (IEEE), 2017, 3439-3446 p., 7989392Conference paper (Refereed)
Abstract [en]

In this work, we present an algorithm that simultaneously searches for a high quality fingertip grasp and a collision-free path for a robot hand-arm system to achieve it. The algorithm combines a bidirectional sampling-based motion planning approach with a hierarchical contact optimization process. Rather than tackling these problems in a decoupled manner, the grasp optimization is guided by the proximity to collision-free configurations explored by the motion planner. We implemented the algorithm for a 13-DoF manipulator and show that it is capable of efficiently planning reachable high quality grasps in cluttered environments. Further, we show that our algorithm outperforms a decoupled integration in terms of planning runtime.

Place, publisher, year, edition, pages
Institute of Electrical and Electronics Engineers (IEEE), 2017. 3439-3446 p., 7989392
Series
Proceedings - IEEE International Conference on Robotics and Automation, ISSN 1050-4729
National Category
Computer Vision and Robotics (Autonomous Systems)
Identifiers
URN: urn:nbn:se:kth:diva-213525DOI: 10.1109/ICRA.2017.7989392Scopus ID: 2-s2.0-85027994091ISBN: 9781509046331 (print)OAI: oai:DiVA.org:kth-213525DiVA: diva2:1138005
Conference
2017 IEEE International Conference on Robotics and Automation, ICRA 2017, Marina Bay Sands International Convention Centre Singapore, Singapore, 29 May 2017 through 3 June 2017
Note

QC 20170904

Available from: 2017-09-04 Created: 2017-09-04 Last updated: 2018-01-13Bibliographically approved

Open Access in DiVA

No full text

Other links

Publisher's full textScopus

Search in DiVA

By author/editor
Haustein, JoshuaHang, KaiyuKragic, Danica
By organisation
Robotics, perception and learning, RPLCentre for Autonomous Systems, CAS
Computer Vision and Robotics (Autonomous Systems)

Search outside of DiVA

GoogleGoogle Scholar

doi
isbn
urn-nbn

Altmetric score

doi
isbn
urn-nbn
Total: 4 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