© 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)|
|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||Proceedings of the 2017 IEEE 24th International Congress on Electronics, Electrical Engineering and Computing, INTERCON 2017|
|Abbreviated title||INTERCON 2017|
|Period||15/08/17 → 17/08/17|