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Coordinated navigation of two agricultural robots in a vineyard: A simulation study – Sensors, vol. 22, no. 23, 9095, 2022

23/11/2022
humain
2022, Journals, Publications, Tegea

Abstract The development of an effective agricultural robot presents various challenges in actuation, localization, navigation, sensing, etc., depending on the prescribed task. Moreover, when multiple robots are engaged in an agricultural task, this requires appropriate coordination strategies to be developed to ensure safe, effective, and efficient operation. This paper presents a simulation study that demonstrates a robust coordination strategy for the navigation of two heterogeneous robots, where one robot is the expert and the second robot is the helper in…

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Considerations for a multi-purpose agrobot design toward automating skillful viticultural tasks: a study in northern Greece vineyards – HAICTA 2022, Athens, Greece

25/09/2022
humain
2022, Publications, Tegea

Abstract Seasonal labor shortages in agriculture are experienced throughout Europe and beyond especially, but not only, during the harvest time when the demand for hands is high as well as urgent. Agrobots have been established as a sustainable solution to support these growing demands due to their capacity to work incessantly, fast as well as with skillful precision.  In the aforementioned context, this work investigates the design of a single multi-purpose robotic system towards automation of a number of skillful…

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Variable selection for the prediction of TSS, pH and TA of intact berries of Thompson seedless grapes from their NIS reflection – SoftCOM 2022, Split, Croatia

24/09/2022
humain
2022, Publications, Tegea
Abstract Wavenumbers of high absolute value of correlation coefficient to Total Soluble Solids (TSS), pH, or Titratable Acidity (TA) were selected from reflection Fourier transform near infrared (FT-NIR) spectra of intact grape berries of the white variety Thompson Seedless. Multiple linear regression (MLR) and partial least squares (PLS) regression were applied to the spectra to construct trained regression models able to predict TSS, pH, and TA. Square Pearson’s correlation coefficient (R2) and the Mean Square Error (MSE) were used to…
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Fuzzy lattice reasoning (FLR) for decision-making on an ontology of constraints toward agricultural robot harvest – FLINS 2022 on Machine learning, Multi agent and Cyber physical systems, Tianjin, China (Best Paper Award)

28/08/2022
humain
2022, Publications, Tegea
Abstract A sustainable production of high-quality agricultural products calls for personalized- rather than for massive- operations. The aforementioned (personalized) operations can be pursued by human-like reasoning applicable per case. The interest here is in agricultural grape robot harvest where a binary decision needs to be taken, given a set of ambiguous constraints represented by a Boolean lattice ontology of inequalities. Fuzzy lattice reasoning (FLR) is employed for decision making. Preliminary experimental results on expert data demonstrate the advantages of the…
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An Overview of End Effectors in Agricultural Robotic Harvesting Systems – Agriculture 2022, 12(8), 1240

17/08/2022
humain
2022, Journals, Publications, Tegea

Abstract In recent years, the agricultural sector has turned to robotic automation to deal with the growing demand for food. Harvesting fruits and vegetables is the most labor-intensive and time-consuming among the main agricultural tasks. However, seasonal labor shortage of experienced workers results in low efficiency of harvesting, food losses, and quality deterioration. Therefore, research efforts focus on the automation of manual harvesting operations. Robotic manipulation of delicate products in unstructured environments is challenging. The development of suitable end effectors…

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