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Combinatorial optimization for hierarchical contact-level grasping
Computer Vision and Active Perception Lab, Centre for Autonomous Systems, School of Computer Science and Communication, KTH Royal Institute of Technology, Stockholm, Sweden.
Computer Vision and Active Perception Lab, Centre for Autonomous Systems, School of Computer Science and Communication, KTH Royal Institute of Technology, Stockholm, Sweden. (AASS)ORCID iD: 0000-0003-3958-6179
Computer Vision and Active Perception Lab, Centre for Autonomous Systems, School of Computer Science and Communication, KTH Royal Institute of Technology, Stockholm, Sweden.
Computer Vision and Active Perception Lab, Centre for Autonomous Systems, School of Computer Science and Communication, KTH Royal Institute of Technology, Stockholm, Sweden.
2014 (English)In: 2014 IEEE International Conference on Robotics and Automation (ICRA), IEEE, 2014, p. 381-388Conference paper, Published paper (Refereed)
Abstract [en]

We address the problem of generating force-closed point contact grasps on complex surfaces and model it as a combinatorial optimization problem. Using a multilevel refinement metaheuristic, we maximize the quality of a grasp subject to a reachability constraint by recursively forming a hierarchy of increasingly coarser optimization problems. A grasp is initialized at the top of the hierarchy and then locally refined until convergence at each level. Our approach efficiently addresses the high dimensional problem of synthesizing stable point contact grasps while resulting in stable grasps from arbitrary initial configurations. Compared to a sampling-based approach, our method yields grasps with higher grasp quality. Empirical results are presented for a set of different objects. We investigate the number of levels in the hierarchy, the computational complexity, and the performance relative to a random sampling baseline approach.

Place, publisher, year, edition, pages
IEEE, 2014. p. 381-388
Series
IEEE International Conference on Robotics and Automation ICRA, ISSN 1050-4729
National Category
Computer Sciences Computer Vision and Robotics (Autonomous Systems)
Identifiers
URN: urn:nbn:se:oru:diva-71565DOI: 10.1109/ICRA.2014.6906885ISI: 000377221100057Scopus ID: 2-s2.0-84929171240OAI: oai:DiVA.org:oru-71565DiVA, id: diva2:1280239
Conference
IEEE International Conference on Robotics and Automation (ICRA), Hong Kong, China, May 31 - June 7, 2014
Note

Best Student Paper Award Finalist

Available from: 2019-01-18 Created: 2019-01-18 Last updated: 2019-01-23Bibliographically approved

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Stork, Johannes Andreas

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CiteExportLink to record
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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
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