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Sensors 2017, 17(4), 808; doi:10.3390/s17040808

Coastal Areas Division and Coverage with Multiple UAVs for Remote Sensing

Robotics, Vision and Control Group, Universidad de Sevilla, Avda. de los Descubrimientos s/n, 41092 Seville, Spain
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Academic Editors: Felipe Gonzalez Toro and Antonios Tsourdos
Received: 23 December 2016 / Revised: 23 March 2017 / Accepted: 6 April 2017 / Published: 9 April 2017
(This article belongs to the Special Issue UAV-Based Remote Sensing)

Abstract

This paper tackles the problems of exact cell decomposition and partitioning of a coastal region for a team of heterogeneous Unmanned Aerial Vehicles (UAVs) with an approach that takes into account the field of view or sensing radius of the sensors on-board. An initial sensor-based exact cell decomposition of the area aids in the partitioning process, which is performed in two steps. In the first step, a growing regions algorithm performs an isotropic partitioning of the area based on the initial locations of the UAVs and their relative capabilities. Then, two novel algorithms are applied to compute an adjustment of this partitioning process, in order to solve deadlock situations that generate non-allocated regions and sub-areas above or below the relative capabilities of the UAVs. Finally, realistic simulations have been conducted for the evaluation of the proposed solution, and the obtained results show that these algorithms can compute valid and sound solutions in complex coastal region scenarios under different setups for the UAVs. View Full-Text
Keywords: remote sensors; Unmanned Aerial Vehicles; area partition; cell decomposition remote sensors; Unmanned Aerial Vehicles; area partition; cell decomposition
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This is an open access article distributed under the Creative Commons Attribution License which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited. (CC BY 4.0).

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MDPI and ACS Style

Balampanis, F.; Maza, I.; Ollero, A. Coastal Areas Division and Coverage with Multiple UAVs for Remote Sensing. Sensors 2017, 17, 808.

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