The use of small unmanned aerial vehicles (UAVs) has successfully found its way to civil applications. A broad variety of models has been developed and commercialized in the past few years and is available today for end users. UAVs fly routes in an autonomous manner, carry cameras for aerial photography, and may transport goods from one place to another. The range of applications is broad, including aerial monitoring of industrial plants and agriculture fields and support for first time responders in case of disasters to quickly assess the situation and coordinate disaster response forces. UAVs can be classified according to their size and weight, flight range, altitude, and engine type. There are fixed-wing vehicles and multicopters. The terms “drone” and “flying robot” are often used as synonyms for a UAV.
It is often beneficial if a team of coordinated UAVs rather than a single UAV is employed. Multiple UAVs can cover a given area faster or take photos from different perspectives at the same time. The development of such multi-UAV systems is still at an early stage and, consequently, profound research efforts are needed.
The project team in Klagenfurt developed a platform for systems that involves such multiple, collaborating UAVs. One of the main applications of interest is capturing an overview aerial image of a given area in order to support first responders in disaster management. “One can describe this as Google Earth in real time,” Bernhard Rinner explains. The basic operation starts with defining the areas of interest on an electronic map which is used to compute routes for the individual UAVs (mission planning). The UAVs then fly over the area of interest and acquire images. The images are sent to the ground station (networking) and mosaicked to a large overview image (sensed data analysis). “The developed system has been tested in several scenarios and it proved to work well under realistic conditions,” researcher Vera Mersheeva says.
Another use case involves employing a network of UAVs for delivery of important goods in remote areas. “Imagine a large disaster area in which medicine is required in some villages, but roads are flooded or destroyed,” Bettstetter argues. The question arises as how the jobs are allocated to many UAVs in a distributed manner based on customer demand and locations of depots. Pasquale Grippa, a PhD student on this topic, is fascinated by the multidisciplinary aspects of his work. “It involves multi-agent systems, scheduling, logistics, queuing theory, and others,” he says.
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