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In the past decade, unmanned aerial vehicles (UAVs) have been widely used in various civilian applications, most of which only require a single UAV. In the near future, it is expected that more and more applications will be enabled by the cooperation of multiple UAVs. To facilitate such applications, it is desirable to utilize a general control platform for cooperative UAVs. However, existing open-source control platforms cannot fulfill such a demand because (1) they only support the leader-follower mode, which limits the design options for fleet control, (2) existing platforms can support only certain UAVs and thus lack of compatibility, and (3) these platforms cannot accurately simulate a flight mission, which may cause a big gap between simulation and real flight. To address these issues, we propose a general control and monitoring platform for cooperative UAV fleet, namely, CoUAV, which provides a set of core cooperation services of UAVs, including synchronization, connectivity management, path planning, energy simulation, etc. To verify the applicability of CoUAV, we design and develop a prototype and we use the new system to perform an emergency search application that aims to complete a task with the minimum flying time. To achieve this goal, we design and implement a path planning service that takes both the UAV network connectivity and coverage into consideration so as to maximize the efficiency of a fleet. Experimental results by both simulation and field test demonstrate that the proposed system is viable.
This study proposes an efficient data collection strategy exploiting a team of Unmanned Aerial Vehicles (UAVs) to monitor and collect the data of a large distributed sensor network usually used for environmental monitoring, meteorology, agriculture,
Swarms of autonomous devices are increasing in ubiquity and size. There are two main trains of thought for controlling devices in such swarms; centralized and distributed control. Centralized platforms achieve higher output quality but result in high
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