Deterministic Method of Visual Servoing: Robust Object Tracking by Drone
This work is part of an application context, focused on the analysis of images flow acquired by a camera embedded in a drone, controlled by a control station. Specifically, we are interested in the coupling vision command, in order to develop a control system that allows an autonomous navigation and operation of the Unmanned Aerial Vehicle in complex environments where the use of visual sensors appears to be essential for moving the drone in a controlled manner but also to be capable of increasing the stability of the UAV. We propose the state of the art in image based visual servoing, focused on the control of unmanned aerial vehicles and allows moving from a current position to a desired position according the observed scene while also improving the flight performance (stability and accuracy) Our contribution will be in the proposal of a control approach capable to tracking an object by introducing the concept of real time and subsequently uses a visual memory in the form of keyframes to automatically reproduce a route already made.
2016 13th International Conference on Computer Graphics, Imaging and Visualization (CGiV)