On the Routing of Unmanned Aerial Vehicles (UAVs) in Precision Farming Sampling Missions

Georgios Dolias, Lefteris Benos and Dionysis Bochtis ()
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Georgios Dolias: Institute for Bio-Economy and Agri-Technology (iBO), Centre for Research and Technology Hellas (CERTH)
Lefteris Benos: Institute for Bio-Economy and Agri-Technology (iBO), Centre for Research and Technology Hellas (CERTH)
Dionysis Bochtis: Institute for Bio-Economy and Agri-Technology (iBO), Centre for Research and Technology Hellas (CERTH)

A chapter in Information and Communication Technologies for Agriculture—Theme III: Decision, 2022, pp 95-124 from Springer

Abstract: Abstract This chapter focuses on a very important aspect of the utilization of unmanned aerial vehicles (simply mentioned as drones) in precision agriculture; the route planning of drones in (spot) sampling operations. In particular, a brief description of the main types of drones used in agriculture along with indicative applications is given based on the relative literature. Subsequently, the challenges that arise from on-field drones routing are discussed by highlighting the commonly adopted approach, namely the Travelling Salesman Problem (TSP). This combinatorial optimization problem is solved by employing algorithms, which can result in optimal or near-optimal solutions. Towards this direction, several algorithms are concisely described. Furthermore, representative demonstrations of drones routing are performed under different scenarios. These scenarios include three different agricultural fields comprising of 50, 83, and 100 visiting points. Several hypotheses are evaluated in silico, by considering the number of drones, the initial and final locations of each route, and various operational constraints. The most efficient results in terms of both distance covered and computation time are presented.

Keywords: UAVs; TSP; Routing; Smart farming (search for similar items in EconPapers)
Date: 2022
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Persistent link: https://EconPapers.repec.org/RePEc:spr:spochp:978-3-030-84152-2_5

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DOI: 10.1007/978-3-030-84152-2_5

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