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

Fu, Changhong and Olivares Méndez, Miguel Ángel and Campoy Cervera, Pascual and Suárez Fernández, Ramón (2013). UAS See-and-Avoid Strategy using a Fuzzy Logic Controller Optimized by Cross-Entropy in Scaling Factors and Membership Functions.. In: "2013 International Conference on Unmanned Aircraft Systems (ICUAS'13)", 28-31 May 2013, Atlanta, GA, USA. ISBN 978-1-4799-0817-2. pp. 532-541.

Description

Title: UAS See-and-Avoid Strategy using a Fuzzy Logic Controller Optimized by Cross-Entropy in Scaling Factors and Membership Functions.
Author/s:
  • Fu, Changhong
  • Olivares Méndez, Miguel Ángel
  • Campoy Cervera, Pascual
  • Suárez Fernández, Ramón
Item Type: Presentation at Congress or Conference (Article)
Event Title: 2013 International Conference on Unmanned Aircraft Systems (ICUAS'13)
Event Dates: 28-31 May 2013
Event Location: Atlanta, GA, USA
Title of Book: 2013 International Conference on Unmanned Aircraft Systems (ICUAS'13). Conference Proceedings
Date: 2013
ISBN: 978-1-4799-0817-2
Subjects:
Faculty: E.T.S.I. Industriales (UPM)
Department: Automática, Ingeniería Electrónica e Informática Industrial [hasta 2014]
UPM's Research Group: Computer Vision Group - Universidad Politécnica de Madrid
Creative Commons Licenses: Recognition - No derivative works - Non commercial

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Abstract

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.

Funding Projects

TypeCodeAcronymLeaderTitle
Government of SpainDPI2010-20751-C02-01CICYTUnspecified, China Scholarship Council (CSC)
FP7UnspecifiedECHORDUnspecifiedUnspecified

More information

Item ID: 37638
DC Identifier: http://oa.upm.es/37638/
OAI Identifier: oai:oa.upm.es:37638
Official URL: http://www.uasconferences.com/
Deposited by: Memoria Investigacion
Deposited on: 10 Feb 2016 15:39
Last Modified: 10 Feb 2016 15:46
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