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Probabilistic consolidation of grasp experience
School of Mechanical Engineering, University of Birmingham, Birmingham, UK.
Department of Computer Science, University of Sheffield, Sheffield, UK.
Centre for Autonomous Systems, CSC, Royal Institute of Technology, Sweden.
Centre for Autonomous Systems, CSC, Royal Institute of Technology, Sweden. (AASS)ORCID iD: 0000-0003-3958-6179
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2016 (English)In: 2016 IEEE International Conference on Robotics and Automation (ICRA), IEEE conference proceedings, 2016, p. 193-200Conference paper, Published paper (Refereed)
Abstract [en]

We present a probabilistic model for joint representation of several sensory modalities and action parameters in a robotic grasping scenario. Our non-linear probabilistic latent variable model encodes relationships between grasp-related parameters, learns the importance of features, and expresses confidence in estimates. The model learns associations between stable and unstable grasps that it experiences during an exploration phase. We demonstrate the applicability of the model for estimating grasp stability, correcting grasps, identifying objects based on tactile imprints and predicting tactile imprints from object-relative gripper poses. We performed experiments on a real platform with both known and novel objects, i.e., objects the robot trained with, and previously unseen objects. Grasp correction had a 75% success rate on known objects, and 73% on new objects. We compared our model to a traditional regression model that succeeded in correcting grasps in only 38% of cases.

Place, publisher, year, edition, pages
IEEE conference proceedings, 2016. p. 193-200
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-71560DOI: 10.1109/ICRA.2016.7487133ISI: 000389516200024Scopus ID: 2-s2.0-84977472359OAI: oai:DiVA.org:oru-71560DiVA, id: diva2:1280236
Conference
IEEE International Conference on Robotics and Automation (ICRA), Stockholm, Sweden, May 16-21, 2016
Funder
EU, Horizon 2020
Note

Funding agency: Engineering and Physical Science Research Council (EPSRC)

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
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