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Diverse Planning for UAV Control and Remote Sensing

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AI Center, Department of Computer Science, Faculty of Electrical Engineering, Czech Technical University in Prague, 166 27 Praha 6, Czech Republic


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Academic Editors: Felipe Gonzalez Toro and Antonios Tsourdos

Abstract Unmanned aerial vehicles UAVs are suited to various remote sensing missions, such as measuring air quality. The conventional method of UAV control is by human operators. Such an approach is limited by the ability of cooperation among the operators controlling larger fleets of UAVs in a shared area. The remedy for this is to increase autonomy of the UAVs in planning their trajectories by considering other UAVs and their plans. To provide such improvement in autonomy, we need better algorithms for generating alternative trajectory variants that the UAV coordination algorithms can utilize. In this article, we define a novel family of multi-UAV sensing problems, solving task allocation of huge number of tasks tens of thousands to a group of configurable UAVs with non-zero weight of equipped sensors comprising the air quality measurement as well together with two base-line solvers. To solve the problem efficiently, we use an algorithm for diverse trajectory generation and integrate it with a solver for the multi-UAV coordination problem. Finally, we experimentally evaluate the multi-UAV sensing problem solver. The evaluation is done on synthetic and real-world-inspired benchmarks in a multi-UAV simulator. Results show that diverse planning is a valuable method for remote sensing applications containing multiple UAVs. View Full-Text

Keywords: diverse planning; UAV; remote sensing diverse planning; UAV; remote sensing

Author: Jan Tožička * and Antonín Komenda

Source: http://mdpi.com/


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