Vitaliy Mezhuyev1,*, Yurii Gunchenko2, Sergey Shvorov3, Dmitry Chyrchenko3
Intelligent Automation & Soft Computing, Vol.26, No.1, pp. 121-132, 2020, DOI:10.31209/2019.100000133
Abstract The widespread distribution of precision farming systems necessitates
improvements in the methods for the control of unmanned harvesting
equipment (UHE). While unmanned aerial vehicles (UAVs) provide an effective
solution to this problem, there are many challenges in the implementation of
technology. This paper considers the problem of identifying optimal routes of
UHE movement as a multicriteria evaluation problem, which can be solved by a
nonlinear scheme of compromises. The proposed method uses machine
learning algorithms and statistical processing of the spectral characteristics
obtained from UAV digital images. Developed method minimizes the resources
needed for a harvesting campaign and reduces the… More >
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