Pouring Skills with Planning and Learning Modeled from Human Demonstrations

Akihiko Yamaguchi, Christopher G. Atkeson, Tsukasa Ogasawara

Research output: Contribution to journalArticlepeer-review

16 Citations (Scopus)

Abstract

We explore how to represent, plan and learn robot pouring. This is a case study of a complex task that has many variations and involves manipulating non-rigid materials such as liquids and granular substances. Variations of pouring we consider are the type of pouring (such as pouring into a glass or spreading a sauce on an object), material, container shapes, initial poses of containers and target amounts. The robot learns to select appropriate behaviors from a library of skills, such as tipping, shaking and tapping, to pour a range of materials from a variety of containers. The robot also learns to select behavioral parameters. Planning methods are used to adapt skills for some variations such as initial poses of containers. We show using simulation and experiments on a PR2 robot that our pouring behavior model is able to plan and learn to handle a wide variety of pouring tasks. This case study is a step towards enabling humanoid robots to perform tasks of daily living.

Original languageEnglish
Article number1550030
JournalInternational Journal of Humanoid Robotics
Volume12
Issue number3
DOIs
Publication statusPublished - 2015 Sep 20
Externally publishedYes

Keywords

  • Pouring
  • learning from demonstration
  • learning from practice
  • planning

ASJC Scopus subject areas

  • Mechanical Engineering
  • Artificial Intelligence

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