Abstract
The paper reports the results of a research on validation and optimization of automatic and semi-automatic guidance systems for agricultural machinery based on Real-Time positioning services provided by GNSS Networks (NRTK). The research is based on experimental campaigns performed on test areas, located in Umbria (central Italy) on the land of six farming companies.
The tests have interested many processes of the agricultural work carried out in different seasons and environmental conditions, by means of agricultural machinery of various size, power and characteristics. For the performance evaluation of different guidance systems and positioning methods, reference solutions obtained in post-processing with geodetic GNSS receivers have been utilized.
To reach generalized conclusions, appropriate parameters have been defined and evaluated in order to compare the quality of the results of tests performed with different equipment and conditions, and to quantify the economic benefits achieved through the GNSS guidance systems. Further tests have been performed to evaluate the ability of machine control systems to acquire a series of useful agronomic and geometric data during the work to be included in a farm-level GIS, including the three-dimensional geometry of the crops, the creation of reports about processes and treatments and the optimization of the machine paths and related agricultural activities.
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Acknowledgements
This research was developed in the frame of Rural Development Plans (PSR) promoted by Umbria Regional Council and financed by EU.
We want to say thanks to the technical partner Topcon Positioning Italy, Cratia-Confagricoltura Umbria and all the farming companies involved in the project: FIA Foundation in Perugia, Blasi, Arnaldo Caprai Winery, Alviero Giovagnoli, Sodalizio of S. Martino, Mastri Birrai Umbri.
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Radicioni, F., Stoppini, A., Brigante, R., Brozzi, A., Tosi, G. (2020). GNSS Network RTK for Automatic Guidance in Agriculture: Testing and Performance Evaluation. In: Gervasi, O., et al. Computational Science and Its Applications – ICCSA 2020. ICCSA 2020. Lecture Notes in Computer Science(), vol 12253. Springer, Cham. https://doi.org/10.1007/978-3-030-58814-4_2
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DOI: https://doi.org/10.1007/978-3-030-58814-4_2
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