[Studies in Computational Intelligence 481] Artur Babiarz, Robert Bieda, Karol Jędrasiak, Aleksander Nawrat (auth.), Aleksander Nawrat, Zygmunt Kuś (eds.) - Vision Based Systemsfor UAV Applications (2013, Sprin

344 Conclusions
Control algorithms are another important issues in development of UAV. There
are three main applications of vision based algorithms in this area. UAV objects
can be controlled by sending commands by human terrestrial operator using gestures.
Systems recognizing gestures might significantly improve the quality of
control. The other approach is to use aerial vision information. However, the biggest
challenges here are stabilization and denoising of the video stream, calibration,
in order to perform distortion compensation, and improvement of intensity of
illumination or acquisition noise, for example due to high temperature of the device
surroundings. The third application of vision based control algorithms is navigation
of UAVs in an unknown dynamically changing environment. Geodesic
terrain maps are commonly used in this area. However, there are a lot of disadvantages
related with this approach. Such maps are often outdated and they are not
include information about some tall buildings or flora. The big problem here is
also connected with the appearance of other flying units in a local environment of
UAVs. Control of the drones and planning a mission using 3D maps is an important
issue and big challenging problem. Therefore, it should be solved in order
to simplify and precise the process of navigation in a dynamically changing
environments.
An important task during designing and construction of UAVs is process of
testing: simulations and real life experiments. The first step of testing is utilization
of data using advanced simulation environments. The UAV navigation algorithms
can be implemented and followed by established trajectory. At the same time, it is
possible to observe video streams acquired from virtual cameras, which are placed
under UAV object. The video stream from a camera should be wirelessly transmit
to human operator using ground base station, and should be encrypted due to the
high risk of wireless data capture. Thus, a significant network bandwidth and dedicated
image and sound compression algorithms are required.
The aim of simulation tests and real life experiments are to obtain positive results
using simulations. Such results are considered as a first stage of development
and improvement of classification and detection algorithms. Multiple sources of
information are used to improve the quality of recognition. But the other problem
is arising here. The increased amount of information sometimes can results in
deterioration of real time processing. Therefore, dimensional reduction and clustering
algorithms should be used to reduce the amount of data.
The area of UAV development is broad and essentially new. Therefore, the algorithms
and methods used in this field should be improved and increased. All of
the presented solutions are supported by analysis of applied techniques, analysis of
new methods and results, and inspiring discussions. The new methods applied in
this area show promising future, however, still there are a lot of challenging tasks
for scientists and developers, which should be discussed and solved.