Title :
See-and-avoid quadcopter using fuzzy control optimized by cross-entropy
Author :
Olivares-Mendez, Miguel A. ; Campoy, Pascual ; Mellado-Bataller, Ignacio ; Mejias, Luis
Author_Institution :
CAR - Centro de Autom. y Robot., Univ. Politec. de Madrid, Madrid, Spain
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.
Keywords :
autonomous aerial vehicles; collision avoidance; entropy; fuzzy control; object detection; optimisation; robot vision; target tracking; Camshift algorithm; ROS-Gazebo 3D simulation; cross-entropy theory; flight trials; fuzzy control; image processing front-end; object detection; object tracking; obstacle avoidance; optimal gains estimation; optimization process; optimized fuzzy visual servoing system; see-and-avoid quadcopter; small quadrotor; unmanned aerial vehicle; Aircraft; Cameras; Image color analysis; Optimization; Probability density function; Robot sensing systems;
Conference_Titel :
Fuzzy Systems (FUZZ-IEEE), 2012 IEEE International Conference on
Conference_Location :
Brisbane, QLD
Print_ISBN :
978-1-4673-1507-4
Electronic_ISBN :
1098-7584
DOI :
10.1109/FUZZ-IEEE.2012.6251179