dc.contributorLópez Sotelo, Jesús Alfonso
dc.creatorGonzález López, Francisco Javier
dc.date.accessioned2018-05-24T13:15:51Z
dc.date.accessioned2022-09-22T18:39:36Z
dc.date.available2018-05-24T13:15:51Z
dc.date.available2022-09-22T18:39:36Z
dc.date.created2018-05-24T13:15:51Z
dc.date.issued2018-03-13
dc.identifierhttp://hdl.handle.net/10614/10162
dc.identifier.urihttp://repositorioslatinoamericanos.uchile.cl/handle/2250/3456090
dc.description.abstractAt present the advances in the different fields that integrate the robotics, have allowed to be promoted in various areas, even outside the environment industrial, constituting new concepts for it, such as the social and cognitive robotics, which in their simplest synthesis seek development of autonomous devices that are companions for beings human beings and can enrich the daily life of people, as well as allow improvement in the quality of life of these. And it is so, that the development of robots humanoids intended for work such as assistance to the sick and people elderly, and attention to the public in various environments such as airports, hotels, shopping centers, etc. It has opened the doors to new fields of research ranging from the design of the same, to the development of techniques interaction with humans. This project proposes the development of a system that integrates functionalities that complement the communication process between human beings and humanoid robots, improving human-humanoid interaction, through the implementation of machine learning algorithms, specifically networks artificial neurons, arranged to execute the recognition of the state of encouragement of people (Happy, Sad, Angry, Surprised, Reflective and Normal) using non-verbal language expressed with body language; as well as the ability to "teach" the humanoid robot nonverbal language with which this can complement verbal messages and interact in a manner consistent with the mood of human beings, and that this can generate its own body gestures. The developed system includes a function based on multilayer neural networks (MLP) used to perform the recognition of mood and classification of the same in the established categories, through the expressed body language using with angular values ​​that describe the orientation of the different body joints, obtained using the Kinect Version 2 sensor, developed by Microsoft. It also includes a function with which you can use a conversation between the user and the Pepper robot, using a system of integrated speech recognition with a response generation tool created on the basis of recurrent neural networks (RNN); which, in turn, taking into account the generated response determines a physical behavior suitable with which humanoid robot Pepper, developed by Aldebaran and Softbank Robotics, can complement the verbal message. A series of movement sequences were developed, using a technique of which the humanoid robot is programmed by imitation, which indicate specific behaviors associated with the different moods that can recognize the system and consistent with the meaning of the conversation. Additionally, a Generative Adverse Network (GAN) model was used, through from which, exploiting its generative functionality, it was possible to create sequences of movement from the sequences generated with the imitation tool, original and different that allow to generate the sensation of naturalness in the execution of the physical behavior reproduced by the robot
dc.languageeng
dc.publisherUniversidad Autónoma de Occidente
dc.publisherIngeniería Mecatrónica
dc.publisherDepartamento de Automática y Electrónica
dc.publisherFacultad de Ingeniería
dc.rightshttps://creativecommons.org/licenses/by-nc/4.0/
dc.rightsinfo:eu-repo/semantics/openAccess
dc.rightsAtribución-NoComercial 4.0 Internacional (CC BY-NC 4.0)
dc.rightsDerechos Reservados - Universidad Autónoma de Occidente
dc.sourceinstname:Universidad Autónoma de Occidente
dc.sourcereponame:Repositorio Institucional UAO
dc.source20 Minutos. Así es Nadine: el robot que podría ser la versión real de C3PO. [Online]. 20minutos. [Accessed in May 9 of 2017]. Available in: www.20minutos.es/noticia/2650255/0/nadine/robot/version-real-c3po/ AliveRobots by Robotrónica. NAO Los robots del futuro son ya una realidad. [Online], aliverobots. [Accessed in May 10 of 2017]. Available in: Disponible en: http://aliverobots.com/nao/ --------. Pepper nos habla, El futuro de la robótica[Online]. aliverobots. [Accessed in May 9 of 2017]. Available in: http://aliverobots.com/robot-pepper/ Ahmedabad. India. [Online]. dspace.nitrkl.ac [Accessed in 20 of November of 2017]. Available in: http://dspace.nitrkl.ac.in/dspace/bitstream/2080/2876/1/2017_HYDRO_MdSaleem_ Review.pdf AMY R. Wagoner., Eric T Matson. A Robust Human-Robot Communication System Using a Natural Language for HARMS. En: The 12th International Conference on Mobile Systems and Pervasive Computing. Procedia Computer Science 56. 2015. p 119-126. ARRABALES MORENO , Raúl. Ciencia Cognitiva, IA y Conciencia Artificial. Robótica Cognitiva. [Online], conscious-robots. [Accessed on May 9 of 2017]. Available in: < http://www.conscious-robots.com/es/2007/08/21/robotica-cognitiva/> CIPRIAN L., Cirpian R., Sorin B., Alin P., Design of a humanoid robot head for studying human-robot interaction. Electronics, Computers and Artificial Intelligence. ECAI – International Conference – 7th Edition. 2015. p. WR15-18 CORRALES NAVARRO Elizabeth. El lenguaje no verbal: un proceso cognitivo superior indispensable para el ser humano. [Online], En: Revista Comunicación, vol. 20, no. 1, enero-junio, 2011, p. 46-51. [Accessed on May 9 of 2017]. Available in: < http://www.redalyc.org/pdf/166/16620943007.pdf> COTA LÓPEZ Pablo Isai. Robótica. Trabajo de acreditación para el curso fundamentos de investigación. Robótica. Tijuana BC. [Online] Instituto Tecnológico de Tijuana. Ingeniería en Sistemas Computacionales. 2011., [Accessed on May 9 of 2017]. Available in: https://sites.google.com/site/sccotalopezpabloisai/home CAROLE Adam, WAFA Johal, Damien Pellier, Humbert Fiorino, Sylvie Pesty. Social Human-Robot Interaction:A New Cognitive and Affective Interaction-Oriented Architecture. En: International Conferenceon Social Robotics, 2016. p.253- 263, 2016 DARWIN, Ch. The Expression of Emotion in Man and Animals [online] darwinonline. 1892 p25[Accessed on May 9 of 2017]. Available in: http://darwinonline.org.uk/content/frameset?pageseq=1&itemID=F1142&viewtype=text . El Telégrafo. Los robots tienden puentes con los humanos. 31 de Agosto de 2016. [Online], El telegrafo. 2016 [Accessed on May 9 of 2017]. Available in: http://www.eltelegrafo.com.ec/noticias/septimo-dia/51/los-robots-tienden-puentescon-los-humanos FERNÁNDEZ LOBOGUERRERO Luz Evelyn. RobotAct. Control de acciones para un actor robótico. [Online], Trabajo de grado realizado para optar por el título de Ingeniero en Sistemas. Bogotá DC. Pontificia Universidad Javeriana. Facultad de Ingeniería. Mayo de 2015. [Accessed on May 9 of 2017]. Available in: <https://repository.javeriana.edu.co/bitstream/handle/10554/16493/FernandezLobo guerreroLuzEvelyn2015.pdf?sequence=1 GARCÍA NÁJERA Abel. Docencia. Temas selectos de ingeniería de software II. Robótica Social. [Online], abelgarcia. [Accessed on May 9 of 2017]. Available in: http://www.abelgarcia.mx/robotica-social GERON. Aurélian. Hand-On Machine Learning with Scikit-Learn and TensorFlow. [Online]. safaribooksonline [Accessed in 22 of November of 2017]. Available in: https://www.safaribooksonline.com/library/view/hands-on-machinelearning/9781491962282/ch04.html GitHub Doc. ChatterBot. Machine Learning, conversation dialog engine. [Online]. chatterbot.readthedocs. [Accessed in 25 of November of 2017]. Available in: http://chatterbot.readthedocs.io/en/stable/setup.html I’oboticko. Emiex3, robot umanoide che fa l´hostess. [Online], [Accessed on May 9 of 2017]. Available in: <https://www.robotiko.it/emiew3-robot-umanoide-hostess/z> IAN J. Goodfellow., Jean Pouget-Abadie., Mehdi Mirza., Bing Xu., David WardeFarly., Sherjil Ozair., Aaron Courville., Yoshua Bengio. Generative Adversarial Nets. [Online]. Université de Montréal. Mibtréal, QC h3C 3J7. [Accessed in 22 of November of 2017]. Available in: http://papers.nips.cc/paper/5423-generativeadversarial-nets.pdf JASON Bell. Machine Learning: Hands-On for Developers and Technical Professionals. [Online]. Indiana. John Wiley & Sons, Inc. 2015. [Accessed in 20 of November of 2017]. Available in: https://doc.lagout.org/science/Artificial%20Intelligence/Machine%20learning/Machi ne%20Learning%20HandsOn%20for%20Developers%20and%20Technical%20Professionals%20%5BBell%2 02014-11-03%5D.pdf KARPATHY., Andrej. CS231n Convolutional Neural Network for Visual Recognition, [Online]. Convolutional Neural Networks (CNNs/ConvNets). [Accessed in 23 of November of 2017]. Available in: http://cs231n.github.io/linear-classify#softmax --------. Greg Brockman., et al. Generative Models. [Online]. blog.openai. [Accessed on 23 of November of 2017]. Available in: https://blog.openai.com/generativemodels/ Kinect for Windows. Human Interface Guidelines v2.0. Introduction. Meet the Kinect for Windows Sensor and SDK. Microsoft Corporation.2014 KRÖSE. Ben, Patrick van der Smagt. An Introduction to Neural Networks. [Online]. The University of Amsterdam. . 9th Edition 1996. [Accessed in 20 of November of 2017]. Available in: https://doc.lagout.org/science/Artificial%20Intelligence/Neural%20networks/An%20 Introduction%20to%20Neural%20Networks%20- %20Patrick%20van%20der%20Smagt.pdf MAGNEANAT-THALMANN Nadia., Yuan Junsong., Thalmann Danie., You BumJae. Context Aware Human-Robot and Human-Agent Interaction. Chapter 2 Body Movement Analysis and Recognition En: Springer International Publishing Switzerland..2016. p 31-53 2016. Microsoft Windows. Reto SDK de Kinect: Detectar posturas con skeletal tracking. [Online]. blogs.msdn.microsoft. 2011 [Accessed in 24 of November of 2017]. Available in: https://blogs.msdn.microsoft.com/esmsdn/2011/08/09/reto-sdk-dekinect-detectar-posturas-con-skeletal-tracking/ MOHD Saleem, Sanat Nalini Sahoo. A reviex on Artificial Neural Networks for Streamflow Prediction. a. [Online]. En: International, L.D. College of Engineering Ahmedabad. 2017. [Accessed in 20 of November of 2017]. Available in: http://dspace.nitrkl.ac.in/dspace/bitstream/2080/2876/1/2017_HYDRO_MdSaleem_ Review.pdf Online Manual. Softbank robotics documentation. Pepper-Documentation. [Online]. Pepper-Developer Guide. Technical Overview. [Accessed in 23 of November of 2017]. Available in: http://doc.aldebaran.com/2-4/home_pepper.html ----------. NAOqi-Developer guide. SDKs. ----------.Pepper-Documentation. Pepper-Developer Guide. Technical Overview. ----------.. Pepper-Developer guide. Kinematics data. Joints. OLAH . Christopher. Understanding LSTM Networks. 2015. [Online]. colah.github. [Accessed in 22 of November of 2017]. Available in: colah.github.io/posts/2015-08- Understanding-LSTMs/ Oriol Vinyals. Quoc V. Le. A Neural Conversation Model. ICML Deep Learning Workshop. asXic:1506.05869v3[cs.CL]. [Online]. arxiv.org [Accessed in 25 of November of 2017]. Available in: https://arxiv.org/pdf/1506.05869v3.pdf Pontificia Universidad Católica del Perú. Escuela de Posgrado. [Online], Entrevista al Dr. Gabriele Trovato: Interacción humano-robot. [Accessed on May 9 of 2017]. Available in: < http://posgrado.pucp.edu.pe/noticia/16788/> Prácticas Farmacéuticas Cátedra de la UNLP – Carrera Farmacéutica. La importancia del lenguaje corporal. [Online], blogs.unlp.edu [Accessed on May 9 of 2017]. Available in: http://blogs.unlp.edu.ar/practicafarmaceutica/2015/08/10/laimportancia-del-lenguaje-corporal/ RAE. Robótica. [Online],Rea [Accessed on May 9 of 2017]. Available in: http://dle.rae.es/srv/fetch?id=WYTm4uf ROSARIO S., Salvatore T., Camelo C., Marcelo G., Shuichi N., Hiroshi I., Antonio C. An android architecture for bio-inspired honest signaling in Human-Humanoid 2017. 258p Softbank Robotics. Who is Pepper? [Online]. ald.softbankrobotics [Accessed in 20 of November of 2017]. Available in: https://www.ald.softbankrobotics.com/en/robots/pepper Thought Pursuits. Cómo leer el lenguaje corporal, y ¿por qué es importante? [Online], thoughtpursuits, 2013 [Accessed on May 9 of 2017]. Available in: http://www.thoughtpursuits.com/es/read-body-language-matters-infographic/ Towards Data Science, sharing concepts, ideas, and codes. Anish Singh Walia. Types of optimization algorithms used in Neural Networks and Ways to optimize Gradient Descent. [Online]. Towards data science.2017 [Accessed in 22 of November of 2017]. Available in: https://towardsdatascience.com/types-ofoptimization-algorithms-used-in-neural-networks-and-ways-to-optimize-gradient95ae5d39529f Universidad Carlos III de Madrid. Inteligencia Artificial y robótica social dan vida a NAO, el robot terapeuta. [Online], portal.uc3m. [Accessed in May 10 of 2017]. Available in: <http://portal.uc3m.es/portal/page/portal/colab_secundaria/divulgativas/Inteligencia _Artificial_Robotica_Social> Wernick, Miles N., Yang Youngyi., Brankov Jovan G.., Yourganov Grigori, Strother Sthepen C., Machine Learning in Medical Imaging. En: Signal Processing Magazine, 2010. Vol 27. N° 4. p. 25-38 Wiki. PyMOLWiki. Transformations. [Online]. pymolwiki.org [Accessed in 24 of November of 2017]. Available in: https://pymolwiki.org/index.php/Transformations Wiki. Wikipedia the free encyclopedia. Body Language. [Online]. wikipedia. [Accessed in 23 of November of 2017]. Available in: https://en.wikipedia.org/wiki/Body_language --------. Euler angles. [Online]. wikipedia. [Accessed in 24 of November of 2017]. Available in: https://en.wikipedia.org/wiki/Euler_angles ---------. Python (programming language). [Online]. programming_language [Accessed in 24 of November of 2017]. Available in: https://en.wikipedia.org/wiki/Python_(programming_language) --------- Quaternion. [Online]. wikipedia. [Accessed in 24 of November of 2017]. Available in: https://en.wikipedia.org/wiki/Quaternion Wiki. Wikipedia the free encyclopedia. Stochastic gradient descent. Extensions and variants. RMSprop. [Online]. [Accessed in 26 of November of 2017]. Available in: https://en.wikipedia.org/wiki/Stochastic_gradient_descent WILDML. Artificial Intelligence, Deep Learning, and NLP. Denny Britz. Recurrent Neural Networks Tutorial, Part 1 – Introduction to RNNs. 2015. [Online]. wildml. [Accessed in 22 of November of 2017]. Available in: www.wildml.com/2015/09/recurrent-neural-networks-tutorial-part-1-introduction-tornns/ WordPress.com. Robótica. Aplicación de la robótica. [Online], nextcomrobotics.wordpress [Accessed on May 9 of 2017]. Available in: https://nextcomrobotics.wordpress.com/campo-de-aplicacion/aplicacion-de-larobotica/ Xataka. Este es Pepper, el primer robot humanoide que aspira a conquistar el mercado masivo. [Online], xataka. [Accessed on May 9 of 2017]. Available in: < https://www.xataka.com/robotica-e-ia/este-es-pepper-el-primer-robot-humanoideque-aspira-a-conquistar-el-mercado-masivo> ZHANG. Anthony Python. Package Index. SpeechRecognition.3.8.1. 2017. [Online]. pypi.python.org [Accessed in 25 of November of 2017]. Available in: https://pypi.python.org/pypi/SpeechRecognition/
dc.subjectIngeniería Mecatrónica
dc.subjectRedes Neuronales Artificiales (MLP)
dc.subjectRedes Neuronales Recurrentes (RNN)
dc.subjectModelo Generativo Adversario (GAN)
dc.subjectRobótica social
dc.subjectRobótica cognitiva
dc.subjectRobots humanoides
dc.subjectInteracción humano-humanoide
dc.subjectReconocimiento de emociones
dc.subjectAprendizaje automático
dc.titleDesarrollo de un sistema de interacción humano-humanoide mediante el reconocimiento y aprendizaje del lenguaje corporal
dc.typeTrabajo de grado - Pregrado


Este ítem pertenece a la siguiente institución