Control visual de un vehiculo aereo autonomo usando deteccion y seguimiento de caracterısticas en espacios exteriores

Resumen

The main goal of this thesis is to build vision-guided autonomous flying
robots. Tasks like feature detection, target tracking, obstacle avoidance
using vision sensors allows such robots to serve as intelligent eyes-in-the-sky
suitable for numerous applications including law enforcement, search and
rescue, aerial mapping and inspection, and movie making. Furthermore,
computer vision may reduce uncertainty and increase versatility and overall
accuracy of robotic tasks which are important concerns in most applications.
We address the visual servoing problem for an Unmanned Aerial
Vehicle (UAV) in outdoor environments, specifically an autonomous robotic
helicopter. We propose vision-based techniques which allow an UAV to
perform maneuvers towards features of interest when GPS has dropouts
(usually in urban areas) or to track a target. We investigate visual servo
control techniques that use velocities of suitable image features parameters
directly to compute the references for the flight control for driving the robot,
i.e, the tasks is specified directly in the sensor workspace. Therefore,
the strategy does not require camera calibration procedures or 3D scene
reconstruction schemes which are subject to errors and demand high processing
power.
Although visual servoing is a well studied problem for ground-based
robots or robotics manipulators operating in 2D environments, is not well
studied for the visual control problem of an UAV such as the one proposed
in this thesis. The approach proposed here was analyzed and validated using
several experimental tests on different platforms. We investigate a number
of factors that influence the performance of the system including processing
frame rate, vibrations, control strategies and environmental conditions such
as light and luminance, background changes, etc. Experiments on the real
autonomous helicopter show that visual servoing approach can be used to control the displacements of an autonomous helicopter vertically, laterally
and longitudinally, and can be used to both, track an external target and
guide the UAV trajectory.