Quad Rotorcraft Control develops original control methods for the
navigation and hovering flight of an autonomous mini-quad-rotor robotic
helicopter. These methods use an imaging system and a combination of
inertial and altitude sensors to localize and guide the movement of the
unmanned aerial vehicle relative to its immediate environment.
The history, classification and applications of UAVs are introduced,
followed by a description of modelling techniques for quad-rotors and
the experimental platform itself. A control strategy for the improvement
of attitude stabilization in quad-rotors is then proposed and tested in
real-time experiments. The strategy, based on the use low-cost
components and with experimentally-established robustness, avoids drift
in the UAV's angular position by the addition of an internal control
loop to each electronic speed controller ensuring that, during hovering
flight, all four motors turn at almost the same speed. The quad-rotor's
Euler angles being very close to the origin, other sensors like GPS or
image-sensing equipment can be incorporated to perform autonomous
positioning or trajectory-tracking tasks.
Two vision-based strategies, each designed to deal with a specific kind
of mission, are introduced and separately tested. The first stabilizes
the quad-rotor over a landing pad on the ground; it extracts the
3-dimensional position using homography estimation and derives
translational velocity by optical flow calculation. The second combines
colour-extraction and line-detection algorithms to control the
quad-rotor's 3-dimensional position and achieves forward velocity
regulation during a road-following task.
In order to estimate the translational-dynamical characteristics of the
quad-rotor (relative position and translational velocity) as they evolve
within a building or other unstructured, GPS-deprived environment,
imaging, inertial and altitude sensors are combined in a state
observer.
The text give the reader a current view of the problems encountered in
UAV control, specifically those relating to quad-rotor flying machines
and it will interest researchers and graduate students working in that
field. The vision-based control strategies presented help the reader to
a better understanding of how an imaging system can be used to obtain
the information required for performance of the hovering and navigation
tasks ubiquitous in rotored UAV operation.
