Path planning to minimise distances and recharging instances for a small fleet of vehicles in an arable field

J. Conesa-Muñoz; J.M. Bengochea-Guevara; A. Ribeiro

Path planning to minimise distances and recharging instances for a small fleet of vehicles in an arable field

in Precision agriculture '13

Autor:innen:

J. Conesa-Muñoz

J. Conesa-Muñoz CAR-CSIC, Carretera de Campo Real, km 0.2, Arganda del Rey, 28500 Madrid, Spain; jesus.conesa@csic.es, jose.bengochea@csic.es, angela.ribeiro@csic.es

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J.M. Bengochea-Guevara

J.M. Bengochea-Guevara CAR-CSIC, Carretera de Campo Real, km 0.2, Arganda del Rey, 28500 Madrid, Spain; jesus.conesa@csic.es, jose.bengochea@csic.es, angela.ribeiro@csic.es

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, und

A. Ribeiro

A. Ribeiro CAR-CSIC, Carretera de Campo Real, km 0.2, Arganda del Rey, 28500 Madrid, Spain; jesus.conesa@csic.es, jose.bengochea@csic.es, angela.ribeiro@csic.es

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Art:: Kapitel

Seiten:: 373–380

DOI:: https://doi.org/10.3920/9789086867783_047

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Autonomous small vehicles may be considered a promising option for collecting field information due to their onboard sensing elements and reduced size, which minimise the vehicles’ impact on crop and soil compaction. However, a small mobile unit has very poor energy autonomy for covering real crop fields with large extensions. A fleet of vehicles could be a solution for obtaining shorter distances. Nevertheless, because these small vehicles are usually electric, the distances to cover in a real field are too long and the vehicles will be forced to recharge their batteries several times during the inspection operation, even if a fleet of such vehicles is considered. Installing recharge points close to the field is a possible solution to address the lack of energy, but important questions arise, including how many recharge points are required and where the points should be established to minimise the distance travelled by the mobile units (and consequently the time) as well as the number of recharges needed. This problem can be stated as an optimisation problem with two main objectives to minimise: the number of recharge points and the distance travelled (and, by extension, the time that the task requires). In this paper, an NSGA-II (non-sorting genetic algorithm II) is used to perform this multi-objective optimisation. The results obtained show that the algorithm is able to find optimal solutions in terms of the cost of the mission (i.e. the combination of the distance travelled and the time spent by the vehicles) and the positions and number of recharge points to install next to the field.

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Precision agriculture '13

ISBN:: 9789086867783

Verleger:: Wageningen Academic

Print-Publikationsdatum:: 01 Nov 2013

Fachgebiete
- Biowissenschaften
  - Allgemein
  - Landwirtschaft und Umwelt

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Path planning to minimise distances and recharging instances for a small fleet of vehicles in an arable field

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Precision agriculture '13

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