Laban-Inspired Task-Constrained Variable Motion Generation on Expressive Aerial Robots

Hang Cui, Catherine Maguire, Amy Elizabeth LaViers Minnick

Research output: Contribution to journalArticlepeer-review

Abstract

This paper presents a method for creating expressive aerial robots through an algorithmic procedure for creating variable motion under given task constraints. This work is informed by the close study of the Laban/Bartenieff movement system, and movement observation from this discipline will provide important analysis of the method, offering descriptive words and fitting contexts—a choreographic frame—for the motion styles produced. User studies that use utilize this qualitative analysis then validate that the method can be used to generate appropriate motion in in-home contexts. The accuracy of an individual descriptive word for the developed motion is up to 77% and context accuracy is up to 83%. A capacity for state discernment from motion profile is essential in the context of projects working toward developing in-home robots.
Original languageEnglish (US)
Article number24
JournalRobotics
Volume8
Issue number2
DOIs
StatePublished - Mar 27 2019

Keywords

  • Expressive robots
  • Laban movement analysis
  • Motion planning

ASJC Scopus subject areas

  • Mechanical Engineering
  • Control and Optimization
  • Artificial Intelligence

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