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Learning Predictive State Representation for In-Hand Manipulation
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.
Computer Vision and Active Perception Lab, Centre for Autonomous Systems, School of Computer Science and Communication, KTH Royal Institute of Technology, Stockholm, Sweden.
2015 (English)In: 2015 IEEE International Conference on Robotics and Automation (ICRA), IEEE conference proceedings, 2015, p. 3207-3214Conference paper, Published paper (Refereed)
Abstract [en]

We study the use of Predictive State Representation (PSR) for modeling of an in-hand manipulation task through interaction with the environment. We extend the original PSR model to a new domain of in-hand manipulation and address the problem of partial observability by introducing new kernel-based features that integrate both actions and observations. The model is learned directly from haptic data and is used to plan series of actions that rotate the object in the hand to a specific configuration by pushing it against a table. Further, we analyze the model's belief states using additional visual data and enable planning of action sequences when the observations are ambiguous. We show that the learned representation is geometrically meaningful by embedding labeled action-observation traces. Suitability for planning is demonstrated by a post-grasp manipulation example that changes the object state to multiple specified target configurations.

Place, publisher, year, edition, pages
IEEE conference proceedings, 2015. p. 3207-3214
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-71562DOI: 10.1109/ICRA.2015.7139641ISI: 000370974903031Scopus ID: 2-s2.0-84938273485OAI: oai:DiVA.org:oru-71562DiVA, id: diva2:1280233
Conference
IEEE International Conference on Robotics and Automation (ICRA), Seattle, WA, USA, May 26-30, 2015
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

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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
  • rtf