Formación educativa en el uso de modelos de inteligencia artificial aplicada a la robótica creativa

Héctor Abrahan Romero Guzmán

doi:10.22490/25394088.10632

Vol. 20 No. 1 (2026)

Published 2026-02-23

license

This work is licensed under a Creative Commons Attribution-NonCommercial-NoDerivatives 4.0 International License.

When the Publicaciones e Investigaciones Journal receives an original study or article from its author(s), whether by email, postal service, or the platforms available for said purpose, know that it may be published in physical or electronic formats in national or international archives, databases, or SIRES. As such, Publications and Research authorizes the reproduction and citation of said material, provided that the description of information is carried out in conformity with bibliographic norms, and mention the corresponding names, authors, article, issue, and pages. Publications and Research, in advance, expresses that the information, concepts, and methods are the responsibility of the author(s). As such, the UNAD does not have any influence whatsoever over that expressed in the manuscript.

Article

Educational training in the use of artificial intelligence models applied to creative robotics

DOI: https://doi.org/10.22490/25394088.10632

Héctor Abrahán Romero Guzmán National Experimental University of the Armed Forces

Abstract
References

This article exposes the critical gap between the theory of artificial intelligence and the practical application of its models in creative robotics, especially in systems with limited computational resources. This lack of resources impedes innovation when projects remain solely simulated, preventing the development of truly autonomous agents. In some contexts, the problem is exacerbated in the Bolivarian Republic of Venezuela due to the shortage of specialized human capital and the need for curricular modernization. Its objective is to design and implement an educational training program that trains educators and students in the principles of AI, project-based learning, and model optimization (TinyML) for deployment on robotic platforms. The research focuses on the use of participatory action research methodology, focused on the management of curricular innovation. Therefore, it is concluded that this training solution is essential to address the shortage of professionals, modernize STEAM curricula, and democratize learning about artificial intelligence, ensuring that the next generation is prepared to lead the artificial intelligence revolution in a socially inclusive and sustainable manner.

keywords: Artificial Intelligence, Robotic, Educational Training, Participatory action research

Bostrom, N. (2014). Superintelligence: Paths, Dangers, Strategies. Oxford University Press. https://books.google.co.ve/books?id=7_H8AwAAQBAJ&printsec=frontcover&hl=es&source=gbs_ge_summary_r&cad=0#v=onepage&q&f=true.

Edge Impulse. (2021). FOMO: Object Detection for Constrained Devices. (Referencia basada en material técnico de Edge Impulse que no suele ser un paper académico formal, sino una técnica desarrollada internamente y documentada en blogs/repositorios). https://edgeimpulse.com.

Goodfellow, I., Bengio, Y., & Courville, A. (2016). Deep Learning. MIT Press. https://www.google.co.ve/books/edition/Deep_Learning/Np9SDQAAQBAJ?hl=es&gbpv=0.

Klopfer, Eric, Justin Reich, Hal Abelson y Cynthia Breazeal. 2024. “IA generativa y educación K-12: una perspectiva del MIT”. Una exploración del MIT de la IA generativa , marzo. https://doi.org/10.21428/e4baedd9.81164b06.

Kosecka, J., et al. (2018). Robot Vision. Springer Handbook of Robotics (2nd ed., pp. 697-742). Springer. https://www.google.co.ve/books/edition/Springer_Handbook_of_Robotics/Xpgi5gSuBxsC?hl=es&gbpv=0.

Pearson Guzmán, J y Julio Contreras, C. (2024). Aprendizaje basado en proyectos (ABP): influencia del ABP en la creatividad de los estudiantes. Universidad de San Buenaventura - Cartagena. https://bibliotecadigital.usb.edu.co/entities/publication/0c10e5a7-21b4-4838-a9a2-41a23ad53a3b.

Pfeifer, R., & Bongard, J. C. (2007). How the Body Shapes the Way We Think: A New View of Intelligence. MIT Press.

Posada Vásquez, A. (2008). Nuevas tecnologías y docentes universitarios en una sociedad de cambio. https://bibliotecadigital.usb.edu.co/entities/publication/ef65eca2-cbb9-4e3c-98fe-33edf11a30f5.

Russell, S. J., & Norvig, P. (2010). Artificial Intelligence: A Modern Approach (3rd ed.). Prentice Hall.EE.UU.pp.32-48,64-81. https://www.google.co.ve/books/edition/_/koFptAEACAAJ?hl=es&sa=X&ved=2ahUKEwijv7qzzZmQAxW2m7AFHYDGMnsQre8FegQIDRAK.

Sandler, M., Howard, A., Zhu, M., Zhmoginov, A., & Chen, L. C. (2018). MobileNetV2: Inverted Residuals and Linear Bottlenecks. Proceedings of the IEEE Conference on Computer Vision and Pattern Recognition(CVPR),4510-4520. https://www.google.co.ve/books/edition/Computer_Vision_ECCV_2022_Workshops/KR6uEAAAQBAJ?hl=es&gbpv=0.

Siciliano, B., & Khatib, O. (Eds.). (2016). Springer Handbook of Robotics (2nd ed.). Springer., EE. UU.pp.71-97,405-447. https://www.google.co.ve/books/edition/Springer_Handbook_of_Robotics/Xpgi5gSuBxsC?hl=es&gbpv=0&kptab=overview.

Sutton, R. S., & Barto, A. G. (2018). Reinforcement Learning: An Introduction (2nd ed.). MIT Press. https://www.google.co.ve/books/edition/Reinforcement_Learning_second_edition/sWV0DwAAQBAJ?hl=es&gbpv=0.

Wang, L., et al. (2020). Human-robot collaboration in manufacturing: A review of key issues and applications. International Journal of Production Research, 58(17), 5225-5246.

Warden, P., & Situnayake, D. (2019). TinyML: Machine Learning with TensorFlow Lite on Arduino and Ultra-Low-Power Microcontrollers. O'Reilly Media. California, EE. UU. pp. 71-97,405-447. https://www.google.co.ve/books/edition/TinyML/tH3EDwAAQBAJ?hl=es&gbpv=0

Yang, G. Z., et al. (2017). The grand challenges of science robotics. Science Robotics, 2(12), eaar7650.

license

How to Cite

Romero Guzmán, H. A. (2026). Educational training in the use of artificial intelligence models applied to creative robotics. Publicaciones E Investigación, 20(1). https://doi.org/10.22490/25394088.10632

Download Citation

Almétricas