Programming by demonstration for the teaching and preservation of intangible cultural heritage

Melissa Montalvo; Eduardo Calle-Ortiz

doi:10.1109/INTERCON.2017.8079713

Programming by demonstration for the teaching and preservation of intangible cultural heritage

Melissa Montalvo, Eduardo Calle-Ortiz

Research Group on Interaction, Robotics and Automatics (GIIRA)

Research output: Contribution to conference › Paper

1 Scopus citations

Abstract

© 2017 IEEE. The present research describes the design and implementation of a programming by demonstration algorithm, where data is taken from a human narrator and then processed and imitated by the social robot Nao. This has been done by the use of artificial neural networks and inverse kinematics algorithms, resulting in a 7.25% trajectory difference when comparing the instructor movements with the robot learned movements. An exploratory study is also presented regarding recent advances in social robotics, affective computation, and human-machine interaction. These subjects are analyzed and an innovative way of integrating them as a tool for the narration and diffusion of legends and oral expressions in risk of disappearance is proposed. This work aims the new generations to renew their interest in traditional oral elements and actively involve them in the preservation and transmission of intangible cultural heritage.

Original language	English (US)
DOIs	https://doi.org/10.1109/INTERCON.2017.8079713
State	Published - 20 Oct 2017
Event	Proceedings of the 2017 IEEE 24th International Congress on Electronics, Electrical Engineering and Computing, INTERCON 2017 - Cusco, Peru Duration: 15 Aug 2017 → 17 Aug 2017

Conference

Conference	Proceedings of the 2017 IEEE 24th International Congress on Electronics, Electrical Engineering and Computing, INTERCON 2017
Abbreviated title	INTERCON 2017
Country/Territory	Peru
City	Cusco
Period	15/08/17 → 17/08/17

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title = "Programming by demonstration for the teaching and preservation of intangible cultural heritage",

abstract = "{\textcopyright} 2017 IEEE. The present research describes the design and implementation of a programming by demonstration algorithm, where data is taken from a human narrator and then processed and imitated by the social robot Nao. This has been done by the use of artificial neural networks and inverse kinematics algorithms, resulting in a 7.25% trajectory difference when comparing the instructor movements with the robot learned movements. An exploratory study is also presented regarding recent advances in social robotics, affective computation, and human-machine interaction. These subjects are analyzed and an innovative way of integrating them as a tool for the narration and diffusion of legends and oral expressions in risk of disappearance is proposed. This work aims the new generations to renew their interest in traditional oral elements and actively involve them in the preservation and transmission of intangible cultural heritage.",

author = "Melissa Montalvo and Eduardo Calle-Ortiz",

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doi = "10.1109/INTERCON.2017.8079713",

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AU - Montalvo, Melissa

AU - Calle-Ortiz, Eduardo

PY - 2017/10/20

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N2 - © 2017 IEEE. The present research describes the design and implementation of a programming by demonstration algorithm, where data is taken from a human narrator and then processed and imitated by the social robot Nao. This has been done by the use of artificial neural networks and inverse kinematics algorithms, resulting in a 7.25% trajectory difference when comparing the instructor movements with the robot learned movements. An exploratory study is also presented regarding recent advances in social robotics, affective computation, and human-machine interaction. These subjects are analyzed and an innovative way of integrating them as a tool for the narration and diffusion of legends and oral expressions in risk of disappearance is proposed. This work aims the new generations to renew their interest in traditional oral elements and actively involve them in the preservation and transmission of intangible cultural heritage.

AB - © 2017 IEEE. The present research describes the design and implementation of a programming by demonstration algorithm, where data is taken from a human narrator and then processed and imitated by the social robot Nao. This has been done by the use of artificial neural networks and inverse kinematics algorithms, resulting in a 7.25% trajectory difference when comparing the instructor movements with the robot learned movements. An exploratory study is also presented regarding recent advances in social robotics, affective computation, and human-machine interaction. These subjects are analyzed and an innovative way of integrating them as a tool for the narration and diffusion of legends and oral expressions in risk of disappearance is proposed. This work aims the new generations to renew their interest in traditional oral elements and actively involve them in the preservation and transmission of intangible cultural heritage.

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DO - 10.1109/INTERCON.2017.8079713

M3 - Paper

T2 - Proceedings of the 2017 IEEE 24th International Congress on Electronics, Electrical Engineering and Computing, INTERCON 2017

Y2 - 15 August 2017 through 17 August 2017

ER -

Programming by demonstration for the teaching and preservation of intangible cultural heritage

Abstract

Conference

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