Reference : See-and-Avoid Quadcopter using Fuzzy Control Optimized by Cross-Entropy

	Document type :	Scientific congresses, symposiums and conference proceedings : Paper published in a book
	Discipline(s) :	Engineering, computing & technology : Computer science Engineering, computing & technology : Electrical & electronics engineering
	To cite this reference:	http://hdl.handle.net/10993/9957

Title :	See-and-Avoid Quadcopter using Fuzzy Control Optimized by Cross-Entropy
Language :	English
Author, co-author :	Olivares Mendez, Miguel Angel [Universidad Politecnica de Madrid, Centro de Automatica y Robotica, Spain > Computer Vision Group]
	Campoy, Pascual [Universidad Politecnica de Madrid, Centro de Automatica y Robotica, Spain > Computer Vision Group]
	Mellado-Bataller, Ignacio [Universidad Politecnica de Madrid, Centro de Automatica y Robotica, Spain > Computer Vision Group]
	Mejias, Luis [Queenland University of Technology (QUT), Brisbane, Australia > Australian Research Center for Aerospace Automation (ARCAA)]
Publication date :	2012
Main document title :	See-and-Avoid Quadcopter using Fuzzy Control Optimized by Cross-Entropy
Publisher :	Ieee
Peer reviewed :	Yes
Audience :	International
City :	New York
Event name :	IEEE International Conference on Fuzzy Systems (FUZZ-IEEE)/International Joint Conference on Neural Networks (IJCNN)/IEEE Congress on Evolutionary Computation (IEEE-CEC)/IEEE World Congress on Computational Intelligence (IEEE-WCCI)
Event date :	JUN 10-15, 2012
Event organizer :	IEEE
Event place (city) :	Brisbane
Event country :	AUSTRALIA
Keywords :	[en] UAV ; Fuzzy Control ; See and Avoid ; control ; navigation ; soft-Computing ; Optimization ; Cross-Entropy
Abstract :	[en] 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 cross-entropy methods is a straightforward way to estimate optimal gains achieving excellent results when tested in real flights.
Permalink :	http://hdl.handle.net/10993/9957
Commentary :	978-1-4673-1506-7
Framework Programme / European Project :	FP7 ; 230797 - ICPUAS - International Cooperation Program for Unmanned Aerial Systems (UAS) Research and Development (ICPUAS)

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