Whitening of greenhouse's roof using drones and Petri net models

The Unmanned Aerial Vehicles (UAVs), commonly known as drones, are significant in the agriculture sphere to automate the work such as: data acquisition, crop spraying among others. This paper proposes a path planning solution for a team of UAVs that is required to whiten a greenhouse's roof, th...

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Bibliographic Details
Published in2022 IEEE 27th International Conference on Emerging Technologies and Factory Automation (ETFA) pp. 1 - 8
Main Authors Hustiu, Sofia, Kloetzer, Marius, Lopez-Martinez, Alejandro, Mahulea, Cristian
Format Conference Proceeding
LanguageEnglish
Published IEEE 06.09.2022
Subjects
Energy consumption
Green products
Mathematical models
mathematical programming
path planning
Petri net
Petri nets
Software
Spraying
Three-dimensional displays
UAV
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Summary:The Unmanned Aerial Vehicles (UAVs), commonly known as drones, are significant in the agriculture sphere to automate the work such as: data acquisition, crop spraying among others. This paper proposes a path planning solution for a team of UAVs that is required to whiten a greenhouse's roof, this problem having both social-economic impact, as well as scientific-technical impact. First, the space around the roof is partitioned into cells based on a 3D cell decomposition technique, labeling the cells including the surface of the roof as regions of interest (ROIs). Based on this representation, a Petri net (PN) model captures the motion of drones, while their trajectories are returned by a Mixed Integer Linear Programming (MILP) problem which optimizes the energy consumption. An adaptable strategy is used such that the MILP problem considers only the available UAVs with enough energy to reach the ROIs. The algorithm is implemented in MATLAB and the simulation results are captured in a video link, evaluating the impact of the size of the team and the precision used for mapping the environment over the running time.
DOI:10.1109/ETFA52439.2022.9921482