Learning pouring skills from demonstration and practice

Akihiko Yamaguchi, Christopher G. Atkeson, Scott Niekum, Tsukasa Ogasawara

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

3 Citations (Scopus)

Abstract

This paper focuses on improving performance with practice for tasks that are difficult to model or plan, such as pouring (manipulating a liquid or granular material such as sugar). We are also interested in tasks that involve the possible use of many skills, such as pouring by tipping, shaking, and tapping. Although our ultimate goal is to learn and optimize skills automatically from demonstration and practice, in this paper, we explore manually obtaining skills from human demonstration, and automatically selecting skills and optimizing continuous parameters for these skills. Behaviors such as pouring, shaking, and tapping are modeled with finite state machines. We unify the pouring and the two shaking skills as a general pouring model. The constructed models are verified by implementing them on a PR2 robot. The robot experiments demonstrate that our approach is able to appropriately generalize knowledge about different pouring skills and optimize behavior parameters.

Original languageEnglish
Title of host publication2014 IEEE-RAS International Conference on Humanoid Robots, Humanoids 2014
PublisherIEEE Computer Society
Pages908-915
Number of pages8
ISBN (Electronic)9781479971749
DOIs
Publication statusPublished - 2015 Feb 12
Externally publishedYes
Event2014 14th IEEE-RAS International Conference on Humanoid Robots, Humanoids 2014 - Madrid, Spain
Duration: 2014 Nov 182014 Nov 20

Publication series

NameIEEE-RAS International Conference on Humanoid Robots
Volume2015-February
ISSN (Print)2164-0572
ISSN (Electronic)2164-0580

Other

Other2014 14th IEEE-RAS International Conference on Humanoid Robots, Humanoids 2014
CountrySpain
CityMadrid
Period14/11/1814/11/20

ASJC Scopus subject areas

  • Artificial Intelligence
  • Computer Vision and Pattern Recognition
  • Hardware and Architecture
  • Human-Computer Interaction
  • Electrical and Electronic Engineering

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