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Global Search with Bernoulli Alternation Kernel for Task-oriented Grasping Informed by Simulation
KTH, School of Electrical Engineering and Computer Science (EECS), Robotics, perception and learning, RPL.ORCID iD: 0000-0002-3018-2445
KTH, School of Electrical Engineering and Computer Science (EECS), Robotics, perception and learning, RPL.
KTH, School of Electrical Engineering and Computer Science (EECS), Robotics, perception and learning, RPL.
KTH, School of Electrical Engineering and Computer Science (EECS), Robotics, perception and learning, RPL.ORCID iD: 0000-0003-2965-2953
2018 (English)Conference paper, Published paper (Refereed)
Abstract [en]

We develop an approach that benefits from large simulated datasets and takes full advantage of the limited online data that is most relevant. We propose a variant of Bayesian optimization that alternates between using informed and uninformed kernels. With this Bernoulli Alternation Kernel we ensure that discrepancies between simulation and reality do not hinder adapting robot control policies online. The proposed approach is applied to a challenging real-world problem of task-oriented grasping with novel objects. Our further contribution is a neural network architecture and training pipeline that use experience from grasping objects in simulation to learn grasp stability scores. We learn task scores from a labeled dataset with a convolutional network, which is used to construct an informed kernel for our variant of Bayesian optimization. Experiments on an ABB Yumi robot with real sensor data demonstrate success of our approach, despite the challenge of fulfilling task requirements and high uncertainty over physical properties of objects.

Place, publisher, year, edition, pages
2018.
National Category
Computer Sciences
Research subject
Computer Science
Identifiers
URN: urn:nbn:se:kth:diva-249696OAI: oai:DiVA.org:kth-249696DiVA, id: diva2:1305572
Conference
2nd Conference on Robot Learning, Zürich, Switzerland, Oct. 29-31 2018
Note

Contribution/Authorship note: Rika Antonova and Mia Kokic contributed equally

QC 20190520

Available from: 2019-04-17 Created: 2019-04-17 Last updated: 2019-05-20Bibliographically approved

Open Access in DiVA

No full text in DiVA

Other links

http://proceedings.mlr.press/v87/antonova18a/antonova18a.pdf

Authority records BETA

Antonova, RikaKokic, MiaStork, Johannes A.Kragic, Danica

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CiteExportLink to record
Permanent link

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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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