ANÁLISIS DE PROTOTIPO DE VEHÍCULO AUTÓNOMO CON BASE EN SISTEMA DE VISIÓN Y BAJO EL CONCEPTO DEL INTERNET DE LAS COSAS EN PLATAFORMA INTEL EDISON (ANALYSIS OF PROTOTYPE OF AUTONOMOUS VEHICLE BASED ON VISION SYSTEM AND UNDER THE CONCEPT OF THE INTERNET OF THINGS IN INTEL EDISON´S PLATFORM)

Enrique Gerardo Hernández Vega, Felipe Eliacim Garay Acuña, Vicente González Navarro, Miguel Ángel Gutiérrez Velázquez

Resumen


Resumen

El creciente campo de investigación que concierne a la autonomía vehicular, demanda el continuo desarrollo de tecnología que permita la maduración de este concepto, manifestando retos de eficiencia cada vez mayores relacionados a hardware y software. Este trabajo presenta el diseño, implementación y prueba de un vehículo autónomo en una plataforma con bajos recursos de cómputo. La primera versión se basa en un sistema de visión para percibir la ruta y obstáculos, algoritmos para la toma de decisiones; incorporando el concepto de modularidad e Internet de las cosas. El vehículo se probó en un entorno controlado (iluminación, cambio de color, obstáculos), teniendo la capacidad de navegar por un camino acotado por dos líneas, con obstáculos no preestablecidos para el sistema. Se argumenta la posibilidad de implementar un algoritmo para detectar líneas curvas eficientemente, clases de objetos y diseñar un control difuso para manejar las instrucciones de conducción.

Palabras Claves: Autonomía vehicular, Internet de las cosas, Sistema de visión.


Abstract

 The constant growth in the investigation field concerning to vehicular autonomy, demands the continuous development of technologies that allow the maturity of this concept, stating efficiency challenges higher every time related to hardware and software matter. The paper presents the design, implementation and testing of an autonomous vehicle in a low resources hardware platform. The first version is vision-based system to perceive the route and obstacles, algorithms for decision taking; gathering the concept of modularity and internet of things. The vehicle was proved in a controlled environment (illumination, color changes, obstacles), having the capability to navigate by a two-line bounded path, with not preset obstacles in the system. It argues the possibility of implementing an algorithm for curved lines detection, object classes and designing a fuzzy control to manage driving instructions.

Keywords: Internet of Things, Self-driving car, Vision system.)


Texto completo:

271-289 PDF

Referencias


Assidiq A., Islam R., Khalifa O., & Khan S. Real time lane detection for autonomous vehicles. International Conference on Computer and Communication Engineering. Kuala Lumpur, Malaysia. May, 2008.

A. S. P., Kharade P., Mandalollu L., Marali K., Savadatti P. Prototype Implementation of IoT based Autonomous Vehicle on Raspberry Pi. Bonfring International Journal of Research in Communication Engineering, Vol. 6, Special Issue, November 2016.

Axhausen K., Ciari F., Hörl S, &. Recent perspectives on the impact of autonomous vehicles. Institute for Transport Planning and Systems. Zürich, Switzerland. September, 2016.

Barea R., Bergasa L., López E., López J., Molinos E., Otero C., Paz E., Revenga P., Romera E., Sánchez P., Sanz R. Desarrollo de un vehículo eléctrico autónomo de código abierto para personas mayores. Jornadas Nacionales de Robótica, junio, 2018.

Bertozzi M., Broggi A., & Fascioli A. Vision-based intelligent vehicles: State of the art and perspectives. Elsevier, Robotics and Autonoumus Systems. June, 2000.

Bimbraw, K. Autonomous Cars: Past, Present and Future - A Review of the Developments in the Last Century, the Present Scenario and the Expected Future of Autonomous Vehicle Technology. 12th International Conference on Informatics in Control, Automation and Robotics. Colmar, Alsace, France. July, 2015.

Chen K., & Tsai W. Vision-based obstacle detection and avoidance for autonomous land vehicle navigation in outdoor roads. Elsevier, Automation in Construction. 2000.

Doshi N., Kathiresan S., Peddagolla Y., Prabhu N. & Zadeh M. On the lane detection for autonomous driving: A computational experiment study on performance of the Edge detectors. ResearchGate. June, 2018.

Forrest A., & Konca M. Autonomous cars and society. Worcester Polytechnic Institute. May, 2007.

Lin S., Hsu C., Skach M., & Zhang Y. The architectural implications of autonomous driving: Constraints and acceleration. Association for Computing Machinery. March, 2018.

SAE International. Taxonomy and Definitions for Terms Related to On-Road Motor Vehicle Automated Driving Systems. United States. January, 2014.

Serain D., Client/Server: Why? What? How? International Seminar on Client/Server Computing. October, 1995.






URL de la licencia: https://creativecommons.org/licenses/by/3.0/deed.es

Barra de separación

Licencia Creative Commons    Pistas Educativas está bajo la Licencia Creative Commons Atribución 3.0 No portada.    

TECNOLÓGICO NACIONAL DE MÉXICO / INSTITUTO TECNOLÓGICO DE CELAYA

Antonio García Cubas Pte #600 esq. Av. Tecnológico, Celaya, Gto. México

Tel. 461 61 17575 Ext 5450 y 5146

pistaseducativas@itcelaya.edu.mx

http://pistaseducativas.celaya.tecnm.mx/index.php/pistas