Navigation Functionalities for an Autonomous UAV Helicopter

composed of three accelerometers and three gyros. An artificial pattern is
placed on the ground and it is used by the image processing system to
calculate the pose of the helicopter. A picture of the pattern is shown in
Fig. 5.1.
Figure 5.1: Pattern used for the vision based autonomous landing.
Vision and inertial sensors are combined together because of their complementarity.
Vision provides drift-free position data, while inertial sensors
provide position, velocity and attitude information at higher frequency but
affected by drift. In fact position, velocity and attitude angles derived from
inertial data alone experience unbounded error growth in time.
Depending on the price of the sensor, the drift of the inertial sensor can
be more or less large. A very expensive inertial navigation unit allows an
airplane to navigate for minutes or even hours without large drift. Usually
military and civilian aircrafts or military submarines are equipped with
such sensors. Small UAVs like the RMAX cannot be equipped with such
accurate sensors. The reason is that the high costs of these sensors would
make the platform too expensive. A second reason is that a small UAV has
limited payload capacity and accurate sensors are usually quite heavy to
be carried on-board a small UAV. This is the reason why for small UAVs it
is common practice to fuse together several relatively cheap sensors which
have different characteristics. Fig. 5.2 shows a classification of inertial
sensor performance. The data is taken from [23].
On the other hand, a vision based landing approach which relies only
on a vision system data suffers of several problems. The vision system is
sensitive to illumination conditions such as sun reflection or shadows which
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