CJ: An intelligent robotic head based on deep learning for HRI

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Resumen

The aim of this article is the design and construction of a robotic head intended for classification and recognition applications using algorithms based on Deep Learning. The robotic head works by performing a classification on a number of 1000 different objects thanks to the use of a convolutional neural network (CNN) trained with ImageNet. On the other hand, applying the transfer learning technique in a CNN, allows the recognition of faces on a database of 185 people. The robotic structure also has a voice recognition system, which allows the user to interact with the robot using different voice commands. The construction of the structure is mainly divided into 3D printed components, servomotors, and an Arduino UNO microcontroller, which oversees all the movement that the structure performs.

Idioma originalInglés
Título de la publicación alojadaIEEE ICA-ACCA 2018 - IEEE International Conference on Automation/23rd Congress of the Chilean Association of Automatic Control
Subtítulo de la publicación alojadaTowards an Industry 4.0 - Proceedings
EditoresCarlos Munoz, Gaston Lefranc, Mario Fernandez-Fernandez, Ernesto Rubio, Cristian Duran-Faundez
EditorialInstitute of Electrical and Electronics Engineers Inc.
ISBN (versión digital)9781538655863
DOI
EstadoPublicada - 10 ene 2019
EventoIEEE International Conference on Automation/23rd Congress of the Chilean Association of Automatic Control: Towards an Industry 4.0, ICA-ACCA 2018 - Greater Concepcion, Chile
Duración: 17 oct 201819 oct 2018

Serie de la publicación

NombreIEEE ICA-ACCA 2018 - IEEE International Conference on Automation/23rd Congress of the Chilean Association of Automatic Control: Towards an Industry 4.0 - Proceedings

Conferencia

ConferenciaIEEE International Conference on Automation/23rd Congress of the Chilean Association of Automatic Control: Towards an Industry 4.0, ICA-ACCA 2018
País/TerritorioChile
CiudadGreater Concepcion
Período17/10/1819/10/18

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