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  • 标题:Laban-Inspired Task-Constrained Variable Motion Generation on Expressive Aerial Robots
  • 本地全文:下载
  • 作者:Hang Cui ; Catherine Maguire ; Amy LaViers
  • 期刊名称:Robotics
  • 电子版ISSN:2218-6581
  • 出版年度:2019
  • 卷号:8
  • 期号:2
  • 页码:1-17
  • DOI:10.3390/robotics8020024
  • 出版社:MDPI Publishing
  • 摘要: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.
  • 关键词:motion planning; Laban movement analysis; expressive robots motion planning ; Laban movement analysis ; expressive robots
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