The shortest path detection for unmanned aerial vehicles via genetic algorithm on aerial imaging of agricultural lands

Year 2018, Volume: 2 Issue: 3, 315 - 319, 15.12.2018

Abdülkadir Gümüşçü , Mehmet Emin Tenekeci , Ahmet Tabanlıoğlu

Abstract

By using unmanned aerial vehicles (UAV) for improving fertility of large
agricultural lands in the GAP region, it is aimed to guide the end users through
processing of the aerial images obtained by using image processing algorithms. The
productivity problem of "Agriculture" sector that has the most
important role in the economic development of the region directly has been solved
in an innovative way by improving the fertility of agricultural lands. Related
to the UAVs used for this process, the most important problem to consider is
limited battery life. Therefore, it is very important to calculate the optimum
route to reduce the flight time and to scan the large agricultural lands in the
shortest time. In this paper, the shortest path problem is optimized by using the
genetic algorithm for scanning large agricultural lands and collecting data. In
the study, the points taken by UAV according to the field of view of the images
are determined. The shortest path has been calculated by using genetic algorithm
so that images can be taken from these determined points within a minimum
flight time.

Keywords

Genetic algorithm, Shortest path problem, Unmanned aerial vehicle

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