UAS See-and-Avoid Strategy using a Fuzzy Logic Controller Optimized by Cross-Entropy in Scaling Factors and Membership Functions

Changhong, Fu; Olivares Méndez, Miguel Ángel; Campoy Cervera, Pascual y Suárez Fernández, Ramón (2013). UAS See-and-Avoid Strategy using a Fuzzy Logic Controller Optimized by Cross-Entropy in Scaling Factors and Membership Functions. En: "2013 International Conference on Unmanned Aircraft Systems (ICUAS)", 28/05/2013 - 31/05/2013, Atlanta, GA. pp. 532-541.

Descripción

Título: UAS See-and-Avoid Strategy using a Fuzzy Logic Controller Optimized by Cross-Entropy in Scaling Factors and Membership Functions
Autor/es:
  • Changhong, Fu
  • Olivares Méndez, Miguel Ángel
  • Campoy Cervera, Pascual
  • Suárez Fernández, Ramón
Tipo de Documento: Ponencia en Congreso o Jornada (Artículo)
Título del Evento: 2013 International Conference on Unmanned Aircraft Systems (ICUAS)
Fechas del Evento: 28/05/2013 - 31/05/2013
Lugar del Evento: Atlanta, GA
Título del Libro: Proceedings Unmanned Aircraft Systems (ICUAS), 2013 International Conference on
Fecha: 2013
Materias:
Palabras Clave Informales: Aircraft Cameras Estimation Fuzzy logic Optimization Sensors Visualization
Escuela: E.T.S.I. Industriales (UPM)
Departamento: Automática, Ingeniería Electrónica e Informática Industrial [hasta 2014]
Licencias Creative Commons: Reconocimiento - Sin obra derivada - No comercial

Texto completo

[img] PDF (Document Portable Format) - Acceso permitido solamente a usuarios en el campus de la UPM - Se necesita un visor de ficheros PDF, como GSview, Xpdf o Adobe Acrobat Reader
Descargar (8MB)

Resumen

This work aims to develop a novel Cross-Entropy (CE) optimization-based fuzzy controller for Unmanned Aerial Monocular Vision-IMU System (UAMVIS) to solve the seeand- avoid problem using its accurate autonomous localization information. The function of this fuzzy controller is regulating the heading of this system to avoid the obstacle, e.g. wall. In the Matlab Simulink-based training stages, the Scaling Factor (SF) is adjusted according to the specified task firstly, and then the Membership Function (MF) is tuned based on the optimized Scaling Factor to further improve the collison avoidance performance. After obtained the optimal SF and MF, 64% of rules has been reduced (from 125 rules to 45 rules), and a large number of real flight tests with a quadcopter have been done. The experimental results show that this approach precisely navigates the system to avoid the obstacle. To our best knowledge, this is the first work to present the optimized fuzzy controller for UAMVIS using Cross-Entropy method in Scaling Factors and Membership Functions optimization.

Más información

ID de Registro: 29609
Identificador DC: http://oa.upm.es/29609/
Identificador OAI: oai:oa.upm.es:29609
Depositado por: Memoria Investigacion
Depositado el: 28 Abr 2015 17:58
Ultima Modificación: 28 Abr 2015 17:59
  • Open Access
  • Open Access
  • Sherpa-Romeo
    Compruebe si la revista anglosajona en la que ha publicado un artículo permite también su publicación en abierto.
  • Dulcinea
    Compruebe si la revista española en la que ha publicado un artículo permite también su publicación en abierto.
  • Recolecta
  • e-ciencia
  • Observatorio I+D+i UPM
  • OpenCourseWare UPM