See-and-avoid quadcopter using fuzzy control optimized by cross-entropy

Olivares Méndez, Miguel Ángel and Campoy Cervera, Pascual and Mellado Bataller, Ignacio and Mejias Alvarez, Luis (2012). See-and-avoid quadcopter using fuzzy control optimized by cross-entropy. In: "IEEE World Congress on Computational Intelligence (WCCI 2012)", 10/06/2012 - 15/06/2012, Brisbane, Australia. pp..

Description

Title: See-and-avoid quadcopter using fuzzy control optimized by cross-entropy
Author/s:
  • Olivares Méndez, Miguel Ángel
  • Campoy Cervera, Pascual
  • Mellado Bataller, Ignacio
  • Mejias Alvarez, Luis
Item Type: Presentation at Congress or Conference (Article)
Event Title: IEEE World Congress on Computational Intelligence (WCCI 2012)
Event Dates: 10/06/2012 - 15/06/2012
Event Location: Brisbane, Australia
Title of Book: IEEE World Congress on Computational Intelligence (WCCI 2012)
Date: 2012
Subjects:
Faculty: E.T.S.I. Industriales (UPM)
Department: Automática, Ingeniería Electrónica e Informática Industrial [hasta 2014]
Creative Commons Licenses: Recognition - No derivative works - Non commercial

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Abstract

In this work we present an optimized fuzzy visual servoing system for obstacle avoidance using an unmanned aerial vehicle. The cross-entropy theory is used to optimise the gains of our controllers. The optimization process was made using the ROS-Gazebo 3D simulation with purposeful extensions developed for our experiments. Visual servoing is achieved through an image processing front-end that uses the Camshift algorithm to detect and track objects in the scene. Experimental flight trials using a small quadrotor were performed to validate the parameters estimated from simulation. The integration of crossentropy methods is a straightforward way to estimate optimal gains achieving excellent results when tested in real flights.

Funding Projects

Type
Code
Acronym
Leader
Title
FP7
230797
ICPUAS
Unspecified
International Cooperation Program for Unmanned Aerial Systems (UAS) Research and Development

More information

Item ID: 19383
DC Identifier: https://oa.upm.es/19383/
OAI Identifier: oai:oa.upm.es:19383
Official URL: http://ieeexplore.ieee.org/xpl/abstractKeywords.js...
Deposited by: Memoria Investigacion
Deposited on: 26 Jan 2014 13:08
Last Modified: 07 Nov 2014 11:04
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