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

Olivares-Mendez, Miguel A., Mejias, Luis, Campoy, Pascual, & Mellado-Bataller, Ignacio (2012) See-and-avoid quadcopter using fuzzy control optimized by cross-entropy. In Proceedings of the 2012 IEEE World Congress on Computational Intelligence (IEEE WCCI 2012), IEEE, International Convention Centre, Brisbane, QLD. (In Press)

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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 cross- entropy methods is a straightforward way to estimate optimal gains achieving excellent results when tested in real flights.

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    ID Code: 50718
    Item Type: Conference Paper
    Additional URLs:
    Keywords: Fuzzy Systems, Cross Entropy, UAV, UAS, Visual Control
    Subjects: Australian and New Zealand Standard Research Classification > INFORMATION AND COMPUTING SCIENCES (080000) > ARTIFICIAL INTELLIGENCE AND IMAGE PROCESSING (080100) > Computer Vision (080104)
    Australian and New Zealand Standard Research Classification > INFORMATION AND COMPUTING SCIENCES (080000) > ARTIFICIAL INTELLIGENCE AND IMAGE PROCESSING (080100) > Neural Evolutionary and Fuzzy Computation (080108)
    Australian and New Zealand Standard Research Classification > ENGINEERING (090000) > AEROSPACE ENGINEERING (090100) > Aircraft Performance and Flight Control Systems (090104)
    Divisions: Current > Research Centres > Australian Research Centre for Aerospace Automation
    Current > Schools > School of Electrical Engineering & Computer Science
    Current > QUT Faculties and Divisions > Science & Engineering Faculty
    Copyright Owner: Copyright 2012 [please consult the author]
    Deposited On: 05 Jun 2012 08:36
    Last Modified: 21 Feb 2013 18:01

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