In recent years, visual navigation of unmanned aerial vehicles (UAVs) has been an active area of research. There is a
large amount of visual information to be processed and transmitted with real-time requirements for the flight scenes
change rapidly. However, it has already become one of the major factors that block the cooperative communication in
multi-UAV visual navigation. The traditional video image orthogonal decomposition methods can not be well adapted to
the multi-UAV visual navigation system, because with the compression ratio increases, there is a sharp decline in video
image quality. This paper proposes a novel visual information sparse decomposition and transmission (VSDT)
framework for multi-UAV visual navigation.
In the framework, aiming at the visual information characteristics, firstly we pre-process the video images by introducing
a multi-scale visual information acquisition mechanism. Then a fast video image sparse decomposition is made for
transmission. It can greatly reduce the original video information amount, while the quality of visual information needed
for navigation is guaranteed. Finally, based on data correlations and feature matching, a real-time transmission scheme is
designed to make the receiver UAV can quickly reconstruct the flight scene information for navigation. The simulated
results are presented and discussed.
The main advantage of this framework lies in the ability to reduce the visual information transmission amount while
ensuring the quality of visual information needed for navigation and solve the cooperative communication problems such
as information lag, data conjunction and match error often encountered in multi-UAV visual navigation environment.