Implementation of an auditory feedback control system on an anthropomorphic flutist robot inspired on the performance of a professional flutist

Jorge Solis, Koichi Taniguchi, Takeshi Ninomiya, Klaus Petersen, Tetsuro Yamamoto, Atsuo Takanishi

Research output: Contribution to journalArticle

15 Citations (Scopus)

Abstract

Up to now, different kinds of musical performance robots (MPRs) have been developed. MPRs are designed to closely reproduce the required motor skills displayed by humans in order to play musical instruments. Our research at Waseda University has been focused on developing an anthropomorphic flutist robot. As a result of our research, the Waseda Flutist Robot No. 4 Refined IV (WF-4RIV) has been designed to mechanically reproduce the human organs involved during a flute-playing performance. Although the WF-4RIV is able to play the flute nearly similar to the performance of an intermediate player, further improvements in terms of cognitive capabilities are still required (i.e., autonomously improve the quality of the sound during performance based on the sound processing). For this purpose, in this paper, we present the implementation of an Auditory Feedback Control System (AFCS) designed to enable the flutist robot to analyze the flute sound during a performance (in a similar way professional flutists practice before a performance is held). The AFCS is composed of three subsystems (which are detailed in this paper): WF-4RIV's Control System, Expressive Music Generator and Pitch Evaluation System. A set of experiments was proposed to verify the effectiveness of the proposed AFCS to control the air pressure and to detect/correct faulty notes during a performance. From the experimental results, we confirm the improvements on the flute sound produced by the robot.

Original languageEnglish
Pages (from-to)1849-1871
Number of pages23
JournalAdvanced Robotics
Volume23
Issue number14
DOIs
Publication statusPublished - 2009 Oct 1

Keywords

  • Air pressure control
  • Feedback error learning
  • Humanoid
  • Music
  • Neural networks

ASJC Scopus subject areas

  • Software
  • Control and Systems Engineering
  • Human-Computer Interaction
  • Hardware and Architecture
  • Computer Science Applications

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