Do what I want, not what I did: Imitation of skills by planning sequences of actions

Chris Paxton, Felix Jonathan, Marin Kobilarov, Gregory D. Hager

Research output: Chapter in Book/Report/Conference proceedingConference contribution

Abstract

We propose a learning-from-demonstration approach for grounding actions from expert data and an algorithm for using these actions to perform a task in new environments. Our approach is based on an application of sampling-based motion planning to search through the tree of discrete, high-level actions constructed from a symbolic representation of a task. Recursive sampling-based planning is used to explore the space of possible continuous-space instantiations of these actions. We demonstrate the utility of our approach with a magnetic structure assembly task, showing that the robot can intelligently select a sequence of actions in different parts of the workspace and in the presence of obstacles. This approach can better adapt to new environments by selecting the correct high-level actions for the particular environment while taking human preferences into account.

Original languageEnglish (US)
Title of host publicationIROS 2016 - 2016 IEEE/RSJ International Conference on Intelligent Robots and Systems
PublisherInstitute of Electrical and Electronics Engineers Inc.
Pages3778-3785
Number of pages8
ISBN (Electronic)9781509037629
DOIs
StatePublished - Nov 28 2016
Event2016 IEEE/RSJ International Conference on Intelligent Robots and Systems, IROS 2016 - Daejeon, Korea, Republic of
Duration: Oct 9 2016Oct 14 2016

Publication series

NameIEEE International Conference on Intelligent Robots and Systems
Volume2016-November
ISSN (Print)2153-0858
ISSN (Electronic)2153-0866

Other

Other2016 IEEE/RSJ International Conference on Intelligent Robots and Systems, IROS 2016
Country/TerritoryKorea, Republic of
CityDaejeon
Period10/9/1610/14/16

ASJC Scopus subject areas

  • Control and Systems Engineering
  • Software
  • Computer Vision and Pattern Recognition
  • Computer Science Applications

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