Towards the Development and Verification of a 3D-Based Advanced Optimized Farm Machinery Trajectory Algorithm

Řezník, Tomáš; Heřman, Lukáš; Klocová, Martina; Leitner, Filip; Pavelka, Tomáš; Leitgeb, Šimon; Trojanová, Kateřina; Štampach, Radim; Moshou, Dimitrios; Mouazen, Abdul Mounem; Alexandridis, Thomas; Hrádek, Jakub; Lukas, Vojtěch; Širůček, Petr

doi:10.3390/s21092980

Cited by 7 publications

(3 citation statements)

References 30 publications

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“…In addition, the 3D data obtained before soil tillage can help plan a conventional tillage operation with the optimisation and minimisation of farming machinery traffic, such as reducing the number of trajectories during the soil tillage, taking into account the obstacles and slopes. The development of traffic farming techniques has been addressed by some authors [66,67] to minimise erosion and soil compaction during a conventional tillage operation. The above analysis shows that the unchanged-area-matching method effectively aligned multi-temporal DTMs obtained from UAV surveys with the minimisation of uncertainties.…”

Section: Co-registration Of Dtmsmentioning

confidence: 99%

Measurement of Soil Tillage Using UAV High-Resolution 3D Data

Rebelo

Nascimento

2021

Remote Sensing

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Remote sensing methodologies could contribute to a more sustainable agriculture, such as monitoring soil preparation for cultivation, which should be done properly, according to the topographic characteristics and the crop’s nature. The objectives of this work are to (1) demonstrate the potential of unmanned aerial vehicle (UAV) technology in the acquisition of 3D data before and after soil tillage, for the quantification of mobilised soil volume; (2) propose a methodology that enables the co-registration of multi-temporal DTMs that were obtained from UAV surveys; and (3) show the relevance of quality control and positional accuracy assessment in processing and results. An unchanged-area-matching method based on multiple linear regression analysis was implemented to reduce the deviation between the Digital Terrain Models (DTMs) to calculate a more reliable mobilised soil volume. The production of DTMs followed the usual photogrammetric-based Structure from Motion (SfM) workflow; the extraction of fill and cut areas was made through raster spatial modelling and statistical tools to support the analysis. Results highlight that the quality of the differential DTM should be ensured for a reliable estimation of areas and mobilised soil volume. This study is a contribution to the use of multi-temporal DTMs produced from different UAV surveys. Furthermore, it demonstrates the potential of UAV data in the understanding of soil variability within precision agriculture.

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Section: Co-registration Of Dtmsmentioning

confidence: 99%

Measurement of Soil Tillage Using UAV High-Resolution 3D Data

Rebelo

Nascimento

2021

Remote Sensing

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“…Based on the application area, various requirements are considered in the CPP problem. For example, in the field of agriculture, the path planning algorithm should result in an "optimal" path that takes into account economic and environmental factors, such as fuel consumption [4], configuration of machinery [15], curvature constraints [16], 3D geometrical representation [17,18], multiple filling points [19], and working time [14]. The CPP problem is based on solving the traveling salesman problem [20] and it is proved that this approach results in solving the NP-hard problem; therefore, it is not possible to obtain an optimal solution in a reasonable time.…”

Section: Introductionmentioning

confidence: 99%

Convolutional Neural Network-Based Approximation of Coverage Path Planning Results for Parking Lots

Kriščiūnas,

Čalnerytė,

Fyleris

et al. 2023

IJGI

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Parking lots have wide variety of shapes because of surrounding environment and the objects inside the parking lot, such as trees, manholes, etc. In the case of paving the parking lot, as much area as possible should be covered by the construction vehicle to reduce the need for manual workforce. Thus, the coverage path planning (CPP) problem is formulated. The CPP of the parking lots is a complex problem with constraints regarding various issues, such as dimensions of the construction vehicle and data processing time and resources. A strategy based on convolutional neural networks (CNNs) for the fast estimation of the CPP’s average track length, standard deviation of track lengths, and number of tracks was suggested in this article. Two datasets of different complexity were generated to analyze the suggested approach. The first case represented a simple case with a working polygon constructed out of several rectangles with applied shear and rotation transformations. The second case represented a complex geometry generated out of rectangles and ellipses, narrow construction area, and obstacles. The results were compared with the linear regression models, with the area of the working polygon as an input. For both generated datasets, the strategy to use an approximator to estimate outcomes led to more accurate results compared to the respective linear regression models. The suggested approach enables us to have rough estimates of a large number of geometries in a short period of time and organize the working process, for example, planning construction time and price, choosing the best decomposition of the working polygon, etc.

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“…With the rapid development of robot technology, it has been increasingly applied in the agricultural field [1]. Due to the high intensity of field operations and complex road conditions, research on robot path planning, road recognition and perception, automatic and optimized navigation and robot arm control are all prerequisites for realizing robot field work [2][3][4][5][6][7][8][9][10]. The weeding and harvesting function systems of field robots have been the most studied, while there is little research on crop disease and insect pest perception, nutrient element content diagnosis and precision fertilizer spraying function systems [10][11][12].…”

Section: Introductionmentioning

confidence: 99%

Spectral Diagnostic Model for Agricultural Robot System Based on Binary Wavelet Algorithm

Tang

Gao

et al. 2022

Sensors

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The application of agricultural robots can liberate labor. The improvement of robot sensing systems is the premise of making it work. At present, more research is being conducted on weeding and harvesting systems of field robot, but less research is being conducted on crop disease and insect pest perception, nutritional element diagnosis and precision fertilizer spraying systems. In this study, the effects of the nitrogen application rate on the absorption and accumulation of nitrogen, phosphorus and potassium in sweet maize were determined. Firstly, linear, parabolic, exponential and logarithmic diagnostic models of nitrogen, phosphorus and potassium contents were constructed by spectral characteristic variables. Secondly, the partial least squares regression and neural network nonlinear diagnosis model of nitrogen, phosphorus and potassium contents were constructed by the high-frequency wavelet sensitivity coefficient of binary wavelet decomposition. The results show that the neural network nonlinear diagnosis model of nitrogen, phosphorus and potassium content based on the high-frequency wavelet sensitivity coefficient of binary wavelet decomposition is better. The R2, MRE and NRMSE of nn of nitrogen, phosphorus and potassium were 0.974, 1.65% and 0.0198; 0.969, 9.02% and 0.1041; and 0.821, 2.16% and 0.0301, respectively. The model can provide growth monitoring for sweet corn and a perception model for the nutrient element perception system of an agricultural robot, while making preliminary preparations for the realization of intelligent and accurate field fertilization.

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Towards the Development and Verification of a 3D-Based Advanced Optimized Farm Machinery Trajectory Algorithm

Cited by 7 publications

References 30 publications

Measurement of Soil Tillage Using UAV High-Resolution 3D Data

Measurement of Soil Tillage Using UAV High-Resolution 3D Data

Convolutional Neural Network-Based Approximation of Coverage Path Planning Results for Parking Lots

Spectral Diagnostic Model for Agricultural Robot System Based on Binary Wavelet Algorithm

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