Observatorio de I+D+i UPM

Descripción
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.
Internacional	Si
Nombre congreso	WCCI 2012 IEEE World Congress on Computational Intelligence
Tipo de participación	960
Lugar del congreso	Brisbane, Australia
Revisores	Si
ISBN o ISSN	CDP08UPM
DOI
Fecha inicio congreso	10/06/2012
Fecha fin congreso	15/06/2012
Desde la página	0
Hasta la página	0
Título de las actas	Proceedings on on Computational Intelligence WCCI 2012 IEEE World Congress

Esta actividad pertenece a memorias de investigación

• Autor: Pascual Campoy Cervera (UPM)
• Autor: Miguel Ángel Olivares Mendez (UPM)

• Creador: Grupo de Investigación: Computer Vision
• Centro o Instituto I+D+i: Centro de Automática y Robótica (CAR). Centro Mixto UPM-CSIC
• Departamento: Automática, Ingeniería Electrónica e Informática Industrial