Tractor Guidance Research Articles

Operating performance of manual, semi-automatic, and automatic tractor guidance systems for precision farming

Operating performance of manual, semi-automatic, and automatic tractor guidance systems for precision farming

Tractor Guidance Systems Benefit From Experienced Operators

CSA NewsVolume 68, Issue 1 p. 19-19 SOCIETY SCIENCE Tractor Guidance Systems Benefit From Experienced Operators First published: 30 November 2022 https://doi.org/10.1002/csan.20918Read the full textAboutPDF ToolsRequest permissionExport citationAdd to favoritesTrack citation ShareShare Give accessShare full text accessShare full-text accessPlease review our Terms and Conditions of Use and check box below to share full-text version of article.I have read and accept the Wiley Online Library Terms and Conditions of UseShareable LinkUse the link below to share a full-text version of this article with your friends and colleagues. Learn more.Copy URL Share a linkShare onFacebookTwitterLinkedInRedditWechat No abstract is available for this article. Volume68, Issue1January 2023Pages 19-19 RelatedInformation

Environmental Impact Assessment of Tractor Guidance Systems Based on Pasture Management Scenarios

HighlightsTractor guidance (TG) reduced the overlaps and gaps during fertilizer and herbicide applications.Production gains with TG on were 2.7% to 6.5% relative to TG off; however, fuel consumption increased.A 5% increase in yield is needed to make tractor guidance environmentally remunerating.Abstract. The use of auto-guidance on tractors and self-propelled machinery improves agricultural production efficiencies by reportedly avoiding negative environmental impacts from over-applying fertilizers and herbicides. Environmental impacts from auto-tractor guidance systems have not been systematically quantified and are difficult to assess at the farm system level. Therefore, this study uses a life cycle-based assessment to quantify the environmental impacts of deploying tractor guidance (TG) over a range of fertility rates, fertilizer sources (organic and inorganic), equipment, and pasture crops through scenarios based on in-field data (collected with and without TG). The use of TG reduced gaps by 7.6% and 10.1% and reduced absolute overlaps by 32.5% and 4.2% during herbicide and fertilizer application, respectively. Estimated production gains with TG on ranged from 2.7% to 6.5% over the baseline (TG off); however, tractor fuel consumption increased when TG was employed. There was high uncertainty for productivity gain estimates; however, under scenario testing with an assumed 15% yield gain, TG resulted in 8% to 12% reduced environmental impacts across all impact categories relative to non-GPS enabled technologies. Future research should be focused on actual yield-based responses from TG, as well as field emissions, operator experience, and resulting water quality. Overall, yield gains were crucial for improved pasture-based system sustainability when using TG because TG results in fewer gaps and overlaps, thereby resulting in greater input use across pasture landscapes. Consequently, more targeted applications of inputs during production may lead to fewer nutrients in water systems and more sustainable production of food. Keywords: Auto-guidance, Forage systems, Life cycle assessment, Poultry litter, Precision agriculture, Small farms.

Evaluation of Plant Distribution Regularity in Sowing With Different Guidance Systems by GPS, GIS and Voronoi Polygons

In this study, sowing was carried out with 3 different tractor guidance methods: operator-controled, GPS-controled and automatic-controled. The optimum nutrient areas required for each plant were evaluated using voronoi polygons. Voronoi polygons were used to obtain nutrient areas. Voronoi polygons were used to obtain living spaces. The plant coordinates taken with CORS-RTK GPS were loaded into the CBS program and the voronoi polygon for each plant was obtained. Comparison of nutrient areas was made with shape coefficients calculated using polygon area and perimeter values. Shape coefficient was 0.731 in operator-controlled application, 0.746 in GPS-controlled application and 0.715 in automatic-controled application. Compared to operator-controlled application, shape coefficients were found to be 2 % more in GPS-controlled application and 2 % less in automatic-controlled application. Although the shape coefficients are relatively less in the automatic-controlled system, it can be seen that better results can be obtained in terms of field success due to the advantages such as low workload on the operator, ease of application at night and improvements in time utilization coefficient. As a result of the statistical analysis, it has been found that there is no difference between the applications and can be used interchangeably. As a result, when the systems are compared with each other, it is seen that the automatic-controlled application is more successful.

Semi-Automatic Guidance vs. Manual Guidance in Agriculture: A Comparison of Work Performance in Wheat Sowing

The use of digital systems in precision agriculture is becoming more and more attractive for farmers at every level. A few years ago, the use of these technologies was limited to large farms, due to the considerable income needed to amortize the large investment required. Although this technology has now become more affordable, there is a lack of scientific data directed to demonstrate how these systems are able to determine quantifiable advantages for farmers. Thus, the transition towards precision agriculture is still very slow. This issue is not just negatively affecting the agriculture economy, but it is also slowing down potential environmental benefits that may result from it. The starting point of precision agriculture can be considered as the introduction of satellite tractor guidance. For instance, with semi-automatic and automatic tractor guidance, farmers can profit from more accuracy and higher machine performance during several farm operations such as plowing, harrowing, sowing, and fertilising. The goal of this study is to compare semi-automatic guidance with manual guidance in wheat sowing, evaluating parameters such as machine performance, seed supply and operational costs of both the configurations.

Tractor path overlap is influenced by field shape and terrain attributes

AbstractTractor overlaps and gaps during field operations reduce production efficiencies; however, studies evaluating linkages between overlaps and field terrain attributes are limited. Our objective is to explore relationships between tractor guidance (TG) systems and field shape and terrain attributes on tractor path overlap. Fields with varying attributes were used for fertilizer (six fields) and herbicide (four fields) applications (with and without TG). Overlap polygon and terrain attributes were overlaid and sampled per 50‐ × 50‐m grid cell. Overlap increased with increasing field irregularities (6 to 11% field area), shorter pass lengths (2 to 19 m2), greater slope (17 to 53 m2), and roughness index (13 to 38 m2) per grid cell. Averaged across slope classes, overlap area decreased 41 to 17 m2 (58% reduction) per grid cell with TG. These results are important for future design of machinery, sensors, and improved TG efficiencies for automated field operations.

Tractor guidance improves production efficiency by reducing overlaps and gaps

AbstractTractor guidance (TG) systems presumably improve agricultural production efficiencies by reducing overlaps and gaps during field operations. However, replicated field studies that calculate TG gains are limited but necessary to estimate efficiencies on small farms (82% of U.S. producers). We applied fertilizer with a wheel spreader and herbicides with a boom sprayer on six and four fields, respectively, with and without TG. This study developed novel postprocessing methodology to calculate spatial coverage efficiency from TG systems. Overlap and gap estimation was implemented using the individual pass polygon method (IPPM). We propose a correction factor to adjust biased estimation of overlap area by IPPM. Results from IPPM suggest TG systems reduced overlaps (up to 6% of field area) and gaps (up to 16%) during field operations and improved overall efficiency up to 20%. Consequently, TG systems lead to reduced input use and in‐field operation time, as well as improved equipment efficiency, leading to potential economic and environmental savings for small‐scale producers.

A decision-support system for analyzing tractor guidance technology

A decision-support system was developed to assist small-scale producers, consultants, and extension agents with analyzing expected yield improvements, input cost savings, and equipment efficiency gains associated with global positioning system guidance on tractors using farm-specific details. Default parameters may be modified to perform partial budgeting and break-even analyses on a whole-farm basis. Findings suggest that this technology is profitable on as few as 49 ha, considered small-scale in the region, and under farm conditions assessed within. Further, tractor guidance is more feasible the more input-intensive the crops (e.g. cotton production vs. pasture maintenance) and the more expensive the equipment (e.g. using newer equipment). Changing input use affects greenhouse gas emissions that are reported as carbon equivalent footprint changes due to tractor guidance. For example, changing to tractors with lower horsepower to save on capital investment needs without changing the size of implement drawn, lowers fuel footprint as long as technically feasible and possible from a perspective of completing field work in a timely manner. Also, using manure instead of synthetic fertilizer, while economically advantageous, will increase the footprint of fertilizer applications given, among other factors, lesser nutrient density and thereby greater handling costs with manures. Quantifying these impacts across a whole farm is cumbersome since tractor guidance affects annual equipment use hours that are difficult to track and yet economically important. Hence, the decision support system was designed to capture farm-specific detail. The ability to perform whole-farm planning and sensitivity analyses in an automated, user-friendly, and flexible fashion is expected to increase technology adoption by small-scale producers.

Economic and Environmental Impact Assessment of Tractor Guidance Technology

Core Ideas Tractor guidance (TG) technology allows for spatially precise input applications. A decision‐support tool was developed to quantify environmental and economic impacts of TG. Greatest C equivalent emission reductions and cost savings occurred with Cotton‐Only scenario. TG was profitable for operations evaluated and led to C equivalent emissions reductions. This tool may improve agricultural sustainability and enhance technology adoption. Tractor guidance technology allows for more spatially precise input applications, which leads to efficiency gains that are difficult to quantify at the systems level. A decision‐support tool, Tractor Guidance Analysis (TGA), was developed to quantify carbon equivalent (CE) emission reductions associated with this technology for three scenarios (500 ha each): (i) cotton (Gossypium hirsutum L.), (ii) soybean [Glycine max (L.) Merr.], and (iii) cotton and soybean mixed. Carbon equivalent emission reductions for cotton, soybean, and mixed enterprises were 27.5, 5.6, and 16.5 kg ha−1, with attendant increases in farm profitability ($68,700, $16,900, and, $42,900, respectively). Tractor guidance led to total farm CE emission reductions of 15.7, 3.5, and 9.6 Mg for cotton, soybean, and mixed operations, respectively. These results highlight that CE reductions are (i) crop specific, (ii) scale dependent, and (iii) equipment and input‐use specific. Consequently, TGA can improve agricultural sustainability by informing users of economic and environmental repercussions of tractor guidance and may thereby enhance technology adoption.

Farmers’ Perception of Precision Farming Technology among Hungarian Farmers

Many technologies have appeared in agriculture to reduce the harmful effects of chemical use. One of these technologies is precision farming technology. Precision farming technology should not be considered as only the latest plant production technology or only a new agro-management tool. It is achieved only when the results of electronics and IT equipment are realized in the variable rate treatments zone-by-zone. The advantages and disadvantages of this technology highly depend on the heterogeneity of soil, the knowledge and attitude of the manager and the staff. This is the reason why opinions about the technology effects are so wide. This paper shows the results of the investigation based on interviews about the adoption and knowledge of precision farming technology among Hungarian crop producers. This technology is mostly used by farms over 300 hectares with young farmers. The most characteristic elements were precision fertilization and tractor guidance. The survey examined three groups of farmers with respect to whether they apply precision farming elements or not. We refer to them as “users”, “planners” and “non-users”. According to the survey, the opinions of the “user” and the “non-user” groups of farmers are not significantly different regarding the impacts of precision farming technology (the main advantages were the change in yield quantity, chemical usage and income). Furthermore, the opinions of the farmers regarding the changes in variable costs resulting from the adoption of precision farming technology were also examined (measured in percent). Box-plot analysis was used for this examination. According to the opinion of the “user” group of farmers, the highest cost savings occurred in fertilizer and herbicide costs.

Aplicação de fertilizantes: tecnologia, eficiência energética e ambiente

The application of mineral fertilizers is an essential process for maintaining soil nutrient levels that are adequate for crop development. Nonetheless, the empirical application of these chemical products originates environmental problems and involves economic and energetic costs. The availability of technologies that support the geo-referenced characterization of soil variability and of the crop needs, the space-time analysis of information, and the variable application of fertilizers requires greater know-how by the farmers in order to sustain their decision making. This article presents a set of technological developments demonstrated in previous works by this research team through which it is possible to optimize the energetic performance of the farm tractor (at the level of the driving support systems, advice on the transmission ratios at the gear box, the management of the engine speed and the power take off), as well as the efficiency of the fertilizer application (use of variable rate technology, VRT, based on GPS tractor guidance systems, sensors and actuators). These two aspects, which on one hand contribute to optimizing the energetic performance of the tractor, and on the other, demonstrate the potential of the new technologies for the differential application of fertilizers, affect the production factors that represent fundamental pillars in a farm and are part of the concepts of sustainable agriculture and of precision agriculture.

Towards an Open Software Platform for Field Robots in Precision Agriculture

Robotics in precision agriculture has the potential to improve competitiveness and increase sustainability compared to current crop production methods and has become an increasingly active area of research. Tractor guidance systems for supervised navigation and implement control have reached the market, and prototypes of field robots performing precision agriculture tasks without human intervention also exist. But research in advanced cognitive perception and behaviour that is required to enable a more efficient, reliable and safe autonomy becomes increasingly demanding due to the growing software complexity. A lack of collaboration between research groups contributes to the problem. Scientific publications describe methods and results from the work, but little field robot software is released and documented for others to use. We hypothesize that a common open software platform tailored to field robots in precision agriculture will significantly decrease development time and resources required to perform experiments due to efficient reuse of existing work across projects and robot platforms. In this work we present the FroboMind software platform and evaluate the performance when applied to precision agriculture tasks.

농업용 트랙터의 작업 시 자동 운전 유도를 위한 횡방향 제어기 설계

본 논문은 작업 시 농업용 트랙터의 운전지원을 위한 강인한 횡방향 제어기를 제안하고자 한다. 자동차와 달리 트랙터의 조향 방식은 유압실린더를 이용함으로써 상대적으로 큰 시간지연을 가지고 있으며 작업 시 지면 환경도 일반 도로와는 다르다. 조향 액추에이터 모델을 포함하는 기구학적 트랙터모델을 기반으로 동적 표면 제어라는 비선형 제어기법을 적용하여 조향 액추에이터의 시간지연 및 노면경사의 변화에 강인한 횡방향 제어기를 설계한다. 마지막으로 상용 트랙터 시뮬레이터를 이용하여 마찰계수가 일정한 주어진 노면 상태에서 조향 액추에이터의 시간 지연 변경이나 오르막 또는 내리막과 같은 지형 조건 변화에 대한 횡방향 제어기의 성능 및 강인성을 검증한다.

Development and Validation of Globally Asymptotically Stable Control Laws for Automatic Tractor Guidance

Automatic guidance of agricultural vehicles requires the use of sensors and control techniques. While the Global Position System (GPS) is widely used as a position sensor, different control laws have been used in the scientific literature based on geometry, heuristics, and models. In this article, two new control laws for navigation control of agricultural tractors were developed with one for following straight lines and the other for tracking circular arcs. These two controllers have virtually the same structure based on the tractor's kinematic model. They have no singularity point in the state space. Also, global asymptotic stability is guaranteed with the control laws. Guidance with the proposed controllers in straight lines and circular arc trajectories was simulated and field-tested. The experiments were performed with a tractor equipped with an automatic GPS guidance system. In both simulation and experiment, the control laws led the tractor to converge to the desired trajectories of straight lines and circular arc paths under three different low speeds of 1, 2, and 3 m/s and four different initial conditions that are 90° apart. The simulation and experimental results show the practical validity of the proposed controllers.

Assessing GNSS correction signals for assisted guidance systems in agricultural vehicles

Accuracy levels achieved with differential global positioning system (DGPS) receivers in agricultural operations depend upon the quality of the correction signal. This study has assessed differential signal error from a Dedicated Base Station, OmniSTAR VBS, European Geostationary Navigation Overlay System, European reference frame-IP for internet protocol (EUREF-IP) and radio navigation satellite aided technique (RASANT). These signals were utilized in guidance assisting systems for agricultural applications, such as tillage, harvesting, planting and spraying, in which GPS receivers were used under dynamic conditions. Simulations of agricultural operations on different days and at different time slots and simultaneously recording the tractor′s geo-position from a DGPS receiver and the tractor′s geo-position from a real-time kinematic (RTK) GPS allowed the comparison of the GPS correction signals. The hardware used for tractor guidance was a lightbar (Trimble model EZ-Guide Plus) system. ANOVA statistics showed a significant difference between the accuracy of the correction signals from different sources. GPS correction signal recommendations to farmers depend upon the accuracy required for the specific operation: (a) Yield monitoring and soil sampling (<1 m) are possible with all the GPS correction signals accessed in any time slot. (b) Broadcast seeding, fertilizer and herbicide application (<0.5 m) are possible for 80% of time with OmniSTAR VBS, 40% of time with RASANT and EUREF-IP and 100% of time with a dedicated base station. (c) Transplanting and drill seeding (<0.04 m) are not possible with the accuracy correction provided by any one of the systems used in this study.

Design and Implementation of a GPS Guidance System for Agricultural Tractors Using Augmented Reality Technology

Current commercial tractor guidance systems present to the driver information to perform agricultural tasks in the best way. This information generally includes a treated zones map referenced to the tractor’s position. Unlike actual guidance systems where the tractor driver must mentally associate treated zone maps and the plot layout, this paper presents a guidance system that using Augmented Reality (AR) technology, allows the tractor driver to see the real plot though eye monitor glasses with the treated zones in a different color. The paper includes a description of the system hardware and software, a real test done with image captures seen by the tractor driver, and a discussion predicting that the historical evolution of guidance systems could involve the use of AR technology in the agricultural guidance and monitoring systems.

Controle de tráfego agrícola e atributos físicos do solo em área cultivada com cana-de-açúcar

O objetivo deste trabalho foi avaliar o efeito do controle de tráfego agrícola na compactação do solo em áreas cultivadas com cana-de-açúcar no sistema de colheita mecanizada. O trabalho foi realizado em delineamento de blocos ao acaso, em parcelas subsubdivididas com os tratamentos: colheita mecanizada tradicional; corte mecanizado com controle de tráfego; e corte mecanizado com controle de tráfego e uso do piloto automático. Os atributos físicos do solo foram avaliados nas camadas de 0,0-0,1, 0,1-0,2 e 0,2-0,3 m de profundidade, na linha de plantio, no local em que o rodado passa e no entrerrodado. Avaliaram-se também os efeitos desses tratamentos sobre a produtividade da cana-de-açucar, respectivamente. O tráfego das máquinas agrícolas aumenta a densidade do solo e diminui o diâmetro médio ponderado dos agregados e a macroporosidade na linha de rodado em relação à linha de plantio, o que causa a degradação cumulativa da qualidade física do solo, ao longo dos anos de cultivo. Os dois anos de controle de tráfego agrícola da colheita não influenciaram os atributos físicos do solo estudados.

Autonomous Guidance of Tractor Along Arbitrary Paths on Sloped Terrain

Autonomous Guidance of Tractor Along Arbitrary Paths on Sloped Terrain

Automatic Tractor Guidance on Sloped Terrain (Part 2)

Automatic Tractor Guidance on Sloped Terrain (Part 2)

Automatic Tractor Guidance on Sloped Terrain (Part 1)

Automatic Tractor Guidance on Sloped Terrain (Part 1)