The anthropomorphic flutist robot WF-4R: from mechanical to perceptual improvements

One of the earliest motivations for developing humanoid robots centered on creating robots that may coexist with humans in environments created for human beings. For several years, at Waseda University, the development of the anthropomorphic flutist player has been focused on improving the musical i...

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Bibliographic Details
Published in2005 IEEE/RSJ International Conference on Intelligent Robots and Systems pp. 64 - 69
Main Authors Solis, J., Chida, K., Isoda, S., Suefuji, K., Arino, C., Takanishi, A.
Format Conference Proceeding
LanguageEnglish
Published IEEE 2005
Subjects
Anthropomorphism
Arm
Cognitive robotics
Education
Educational robots
Hidden Markov Model
Hidden Markov models
Human robot interaction
Humanoid Robot
Humanoid robots
Mechanical engineering
music
skill transfer system
Speech recognition
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Summary:One of the earliest motivations for developing humanoid robots centered on creating robots that may coexist with humans in environments created for human beings. For several years, at Waseda University, the development of the anthropomorphic flutist player has been focused on improving the musical interaction between the human and the robot to clarify the human flute playing and to propose novel assisted music teaching tools. In this paper, a new architecture for autonomously transferring skills from robot to human using the flutist robot is introduced. Furthermore, the new version of the flutist robot, the WF-4R (Waseda Flutist No.4 Refined) is presented; where the arm system was added to assure the positioning accuracy of the flute and the development of a melody recognition system to enable the robot to interact with students at the same logical level of perception. An experimental setup has been performed in order to verify the effectiveness of both mechanical and perceptual systems. As a result, using the arms system, we have assured the repetitiveness of the flute positioning. Furthermore, the implemented music recognition system was able to recognize the melody of flutist players (an overall recognition rate of 90%); demonstrating that HMM (usually used for speech recognition) is also effective for flute melody identification.
ISBN:0780389123
9780780389120
ISSN:2153-0858
2153-0866
DOI:10.1109/IROS.2005.1545259