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The interactive robotic percussionist: new developments in form, mechanics, perception and interaction design

Published:10 March 2007Publication History

ABSTRACT

We present new developments in the improvisational robotic percussionist project, aimed at improving human-robot interaction through design, mechanics, and perceptual modeling. Our robot, named Haile, listens to live human players, analyzes perceptual aspects in their playing in real-time, and uses the product of this analysis to play along in a collaborative and improvisatory manner. It is designed to combine the benefits of computational power in algorithmic music with the expression and visual interactivity of acoustic playing. Haile's new features include an anthropomorphic form, a linear-motor based robotic arm, a novel perceptual modeling implementation, and a number of new interaction schemes. The paper begins with an overview of related work and a presentation of goals and challenges based on Haile's original design. We then describe new developments in physical design, mechanics, perceptual implementation, and interaction design, aimed at improving human-robot interactions with Haile. The paper concludes with a description of a user study, conducted in an effort to evaluate the new functionalities and their effectiveness in facilitating expressive musical human-robot interaction. The results of the study show correlation between human's and Haile's rhythmic perception as well as user satisfaction regarding Haile's perceptual and mechanical abilties. The study also indicates areas for improvement such as the need for better timbre and loudness control and more advance and responsive interaction schemes.

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      cover image ACM Conferences
      HRI '07: Proceedings of the ACM/IEEE international conference on Human-robot interaction
      March 2007
      392 pages
      ISBN:9781595936172
      DOI:10.1145/1228716

      Copyright © 2007 ACM

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      Publication History

      • Published: 10 March 2007

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      HRI '07 Paper Acceptance Rate22of101submissions,22%Overall Acceptance Rate242of1,000submissions,24%

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