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 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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