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Publication
Enxame de Drones:
| Name: | Description: | Size: | Format: | |
|---|---|---|---|---|
| 2.75 MB | Adobe PDF |
Abstract(s)
The use of Unmanned Aerial Vehicles (UAVs) in military and police contexts has been drastically in
creasing in recent years, both individually and in swarms. One of the tasks they can perform is area
coverage, which can later be directed towards a Search and Rescue (SAR) operation or forest and
urban surveillance.
This dissertation aims to find the optimized solution with minimum time for a Vehicle Routing Problem
(VRP). To achieve this, an optimization problem is formulated using a Mixed-Integer Linear Programming
(MILP) approach to find the minimum time value. The solution is tested for convex areas separated by
sweep segments parallel to each other, thus generating a back and forth sweep pattern. It is also tested
for non-convex areas that are decomposed through Delaunay triangulation.
The methods were validated in Python, and it was found that the MILP formulation is essential to
achieve the minimum time. Area coverage for non-convex areas, in most cases, obtained lower time va
lues, which is important to get the mission completed faster, when compared to convex polygon method.
However, some weaknesses were observed regarding the division of flight time for each UAV.
Description
Keywords
VANT Cobertura de ´ Area MILP Tempo mínimo Triangulação de Delaunay.