Unmanned Ground Vehicles for Smart Farms

Forecasts of world population increases in the coming decades demand new production processes that are more efficient, safer, and less destructive to the environment. Industries are working to fulfill this mission by developing the smart factory concept. The agriculture world should follow industry leadership and develop approaches to implement the smart farm concept. One of the most vital elements that must be configured to meet the requirements of the new smart farms is the unmanned ground vehicles (UGV). Thus, this chapter focuses on the characteristics that the UGVs must have to function efficiently in this type of future farm. Two main approaches are discussed: automating conventional vehicles and developing specifically designed mobile platforms. The latter includes both wheeled and wheel-legged robots and an analysis of their adaptability to terrain and crops

Sistema GPS de guiado manual para vehículos agrícolas

In this paper, the performance of a manual GPS guidance system to assist farming operations is evaluated. The distribution of granular fertilizer was simulated in order to discretize areas with excessive application of fertilizers and areas with fertilizer application rates below the intended rate. The path of travel followed by a tractor with the manual GPS guidance system was analysed and compared with a commercial parallel tracking system and without guidance assistance. In addition, the analysis evaluated how the use of manual GPS guidance systems improves the performance of field operations that require large distances between passes. Under the experimental conditions used, the best results were obtained using a commercial parallel tracking system but, for our purposes, small differences were observed between the results obtained with the commercial system and the results obtained with the developed manual GPS guidance system, getting pass-to-pass average error values of 0.26 and 0.73 m, respectively. The results obtained with both systems were significantly better than the results obtained when no guidance assistance was used. In our trials, area with appropriate fertilizer rate was clearly increased when guidance assistance was used. Values of area with correct fertilizer rate applied ranged between 87% with commercial parallel tracking and 59% without guidance assistance. The use of the manual GPS guidance system presented in this paper has proved sufficient to obtain good results for mechanical fertilizer spreadingEn este trabajo se ha evaluado un sistema de asistencia al guiado manual para la realización de labores agrícolas. Se simuló la distribución de fertilizante granulado con el objetivo de discretizar áreas con excesiva cantidad de fertilizante y áreas con cantidades inferiores a las previstas. Se comparó la trayectoria seguida por un tractor utilizando el sistema GPS de asistencia al guiado manual con un sistema comercial de guiado paralelo, y sin asistencia al guiado. Nuestro análisis ha permitido evaluar las mejoras que estos sistemas suponen para la realización de labores que requieran elevadas distancias entre pasadas. En nuestras condiciones, los mejores resultados se obtuvieron con un sistema comercial de guiado paralelo, si bien, considerando nuestro propósito, las diferencias fueron reducidas respecto a las obtenidas con el sistema de asistencia al guiado manual desarrollado, con valores medios de error pasada a pasada de 0,26 y 0,73 m, respectivamente. Los resultados obtenidos con ambos sistemas fueron significativamente mejores que los obtenidos cuando no se utiliza ningún sistema de asistencia. En nuestros ensayos, el área con dosis adecuadas de fertilizante se incrementó de forma clara con la utilización del sistema de asistencia al guiado manual. Los valores de superficie con dosis correctas de fertilizante aplicado oscilaron entre el 87% con el sistema comercial de guiado paralelo y el 59% sin asistencia al guiado. Los resultados obtenidos evidencian que el sistema de asistencia al guiado manual desarrollado es válido para la aplicación mecánica de fertilizantesFinancial support for the research was provided by the co-operative “Os Irmandiños S.C.G.” and the “Dirección Xeral de Investigación e Desenvolvemento da Xunta de Galicia” under project no. PGIDIT03RAG14ES

Advanced Non-Chemical and Close to Plant Weed Control system for Organic Agriculture

Use of chemical has been reduced in agriculture for controlling weeds emergence. The use of alternative systems, such as cultural practices (mulching, flame, intercropping etc.) and mechanical system (hoe, tine etc.) has been introduced by various researchers. Automation technique based on sensors controlled system has enhanced the efficiency of the mechanical system for weed control. Mostly, low cost image acquisition sensors and optical sensor to detect the plant ensuring swift operation of vehicles close the crop plants to remove competitive weeds. The available system need to be evaluated to get best possible system for close to plant (CTP) weed removal. In the study various non-chemical weed control measures has been explored and 30 mechanical tools for CTP were evaluated. High precision tillage solutions and thermal weed control by pulsed lasers for eradication of stem or main shoot were found to be the most promising weed control concepts for CTP operation

Tramline farming systems technical manual

Tramline farming improves farm production and efficiency by controlling traffic and confining compaction to permanent tramlines and reducing overlap. This manual will help you develop your farming system to get the tramline farming benefits. The manual contains information on the principles and techniques of implementing a tramline farming system. There are many options available, so you can tailor the system to suit your own farm. In eastern Australia, controlled traffic farming (CTF) is another term used for permanent wheel track farming. The system is based on bare, straight tramlines. The term tramline farming is more commonly used in Western Australia where the system is closer to the original European concept of using bare tramlines for spraying only to avoid weed and soil erosion problems. Although most tramline farmers work in straight lines, some Australian growers, mostly from Western Australia, have shown that tramline farming can be worked successfully round and round. The terms tramline farming and controlled traffic farming can be used interchangeably. For the purpose of this manual we will refer to tramline farming.https://researchlibrary.agric.wa.gov.au/bulletins/1192/thumbnail.jp

Sistem Pengendali Kemudi Traktor Otomatis Empat Roda pada Pengujian Lintasan Lurus

Penelitian ini merupakan penelitian pengembangan traktor otomatis. Meskipun penelitian mengenai traktor otomatis telah banyak dilakukan, namun pengembangan masih terus dilakukan untuk mendapatkan presisi yang lebih tinggi dan metode yang optimal. Tujuan penelitian ini adalah mengembangkan sistem pengendali kemudi traktor agar dapat mengikuti jalur kerja lintasan lurus ketika melakukan kegiatan pengolahan tanah. Model yang dikembangkan harus mampu menghitung sudut setir koreksi dari posisi traktor agar traktor mampu berjalan pada lintasan lurus yang telah ditentukan. Arah pergerakan traktor diketahui dari perbandingan dua posisi traktor yang diperoleh dari RTK DGPS. Algoritma pengendalian terdiri dari susunan perintah-perintah untuk mengendalikan traktor bergerak mengikuti lintasan acuan. Simulasi dilakukan untuk mengetahui kemampuan algoritma yang telah dibuat untuk mengendalikan traktor agar dapat berjalan mengikuti lintasan acuan. Kemampuan algoritma tersebut kemudian diuji dalam kondisi riil dilapangan pada lintasan lurus sepanjang 30 m dengan kecepatan traktor 0.5 m/s. Hasil pengujian di lapangan diperoleh tingkat akurasi kinerja kontrol sebesar 97.13% dan besar simpangan rata-rata terhadap lintasan acuan sebesar 8.62 cm

Paikkakohtainen säätö kasvintuotannossa

The aims of this work were to get answers to the following three questions: (1) What are the potentialities of coordinate-based field crop production? (2) What are the requirements for the method of attaching field crop information to a coordinate system? (3) What are the possible solutions? The work was focused on the effects of positioning quality. In PDC (Position Dependent Control) positioning is needed to target the inputs and to relate inputs and outputs accurately to each other. Systems analysis was used to accomplish a mathematical model of the position dependent control system. The model developed describes a system which consists of models for the positioning method and the target. An accuracy requirement of ±5 meters for N-fertilization was set with the developed model. The results from Keimola gave information on the variability of soil and wheat yield. Regressions for individual input variables and multiple regressions calculated for whole sample lines (á 50 m) were low (r2Koordinaattiin sidotussa peltoviljelyssä kaikki tuotannon suunnitteluun ja toteutukseen liittyvä tieto kohdistuu paikkakoordinaateilla rajattuihin alueisiin, tuotantopaikkoihin. Tutkimuksen tavoitteena oli saada vastaukset seuraaviin kysymyksiin: 1. Millainen potentiaalinen käyttö on koordinaattiin sidotulla peltoviljelyllä? 2. Mitä vaatimuksia koordinaattiin sidontaan käytetyn menetelmän tulee täyttää? 3. Mitä mahdollisia ratkaisumalleja voidaan käyttää? Pellolla kasvuolosuhteet vaihtelevat lyhyilläkin etäisyyksillä. Keimolassa tehdyn kenttäkokeen perusteella normaalissa, näennäisesti hyvin tasaisessa kevätvehnäkasvustossa sato vaihteli voimakkaasti. Mittauksessa käytettiin 0,25 x 0,25 metrin näytealaa, jolta sato kerättiin kokonaisnäytteinä. Samasta kohdasta otettiin viljavuusnäytteet. Satonäytteitä otettiin kahdesta 50 metrin mittaisesta linjasta 0,5 metrin välein, ts. näytteeseen tuli puolet linjan vehnästä. Saatu aineisto osoittautui erittäin vaihtelevaksi. Koordinaattiin sitomisen vaikutusta simuloitiin valiten Keimolasta saadusta aineistosta alueita, joiden aineistoille laskettiin paikalliset matemaattiset mallit. Yhtenä koejäsenenä oli satotasoon perustuva alueen valinta. Selvästi parhaat ennusteet saatiin kuitenkin matkaan sidotulla alueen valinnalla. Tästä voitiin päätellä, että satotasot eivät ennusta maaperän ominaisuuksia vaan päinvastoin: tietty paikka maassa tuottaa sille ominaisen sadon. Tutkimuksessa käytettiin matemaattisia malleja simuloitaessa erilaisten tuotantopanosten kohdentamistarkkuuden vaikutusta. Kohteena oleva alue pellolla, tuotantopaikka, mallinnettiin sadonmuodostuksen ja huuhtoutuman suhteen. Mallissa tuotantopaikkaan annettava käsittely kuvattiin vaikutuskuvioiden avulla, Paikannusvirheen ansiosta vaikutuskuvion kohdentamisessa esiintyy virheitä, joiden ansiosta tuotantopaikat saavat vääriä käsittelyn tasoja. Simuloinnissa selvitettiin erilaisten paikannusvirheiden vaikutusta tuotantopaikasta saatavaan sato- ja huuhtoumatulokseen. Tulosten perusteella saadaan maksimi paikannusvirheet eri tilanteissa. Paikannuslaitteet ovat keskeisessä asemassa koordinaattiin sidotussa viljelyssä, Paikannuslaitekokeissa käytettiin satelliittinavigointilaitteistoja. Vuonna 1990/1991 kokeissa oli geodeettinen GPS (Global Positioning System) laitteisto jossa käytettiin differentiaalilaskentaa jälkikäteen. Vuosina 1993 ja 1994 kokeissa olivat reaaliaikaiseen differentiaalikorjaukseen kykenevät laitteet. Laitteet testattiin tarkoitusta varten tarkasti mitatulla koeajoreitillä Viikissä. Lisäksi vuonna 1993 tehtiin maantie- ja kaupunkiajoja. Vuonna 1994 laitteistoa testattiin edellisten lisäksi käytännön kylvötyön yhteydessä. Tulosten mukaan DGPS (Differential Global Positioning System) on tarpeeksi tarkka koordinaattiin sidottuun viljelyyn. Paikannustarkkuus on normaaliolosuhteissa nykyisellä satelliittikonstellaatiolla parempi kuin vaatimuksena ollut ±5 metriä. Kirjallisuuden ja tutkimustulosten perusteella on selvää, että pellon vaihtelun hallinta ei ole mahdollista muutoin kuin siten, että peltoa viljellään paikkakoordinaattiin sidottuina tuotantopaikkoina. Viljelyyn liittyvät tiedot sidotaan paikkoihin ja työkoneita säädetään näihin kohteisiin yksilöllisesti tehdyn suunnitelman mukaisesti. Tekniikassa on tähän käyttökelpoisia ratkaisuja. Eräs toimiva ratkaisumalli on paikkatietojärjestelmä (GIS) yhdistettynä tiedonkeruuseen, laskentaan ja paikkakohtaiseen säätöön. DGPS satelliittinavigointi sopii tämän järjestelmän paikannusmenetelmäksi. Peltoviljelyssä esiintyviin eri paikannustehtäviin on saatavilla tarpeeksi tarkkoja GPS-laitteita. Paikkakohtainen säätö edellyttää normaalia huomattavasti joustavammin säädettäviä työkoneita. Lisäksi tarvitaan suunnitteluohjelmistoja, jotka käyttävät tuotantopaikkamalleja. Potentiaalisia laitteita ja menetelmiä on jo nyt olemassa kaikkiin paikkakohtaisen säädön osiin. Ongelmaksi muodostuukin niiden yhteenliittäminen toimivaksi järjestelmäksi, joka on myös taloudellisesti kestävällä pohjalla. Tämän jälkeenkin jäämme miettimään, miten tuotantopaikkoja tulisi käsitellä aikaansaadulla järjestelmällä. Kysymys voidaan muotoilla esimerkiksi seuraavasti: mikä on kestävän kehityksen periaatteen mukaista säätöä

Development of an inexpensive guidance system for agricultural purposes

Robotics is a rapidly growing technology and robots have pervaded into most of the industries. Robotics and automation are designed to remove the human factor from the labor intensive and monotonous work and thereby decrease the associated costs. The application of robotics to agriculture is fairly recent. Robotic applications in agriculture vary from autonomous row-guidance tractors to fruit picking robots. Similarly, soil testing and soil sampling is one area in agriculture where automation of tasks and the employment of an autonomous robot would be of great use to consultants and farmers employing site specific farming techniques. Soil testing is an important part of farming used to determine the average nutrient status in a field and to obtain a measure of nutrient availability in the field. Fertilizers and other nutrients are applied to the fields based on different soil tests. Site specific farming is greatly dependent on soil testing and can result in increased yield, reduced cost and reduced water pollution. Soil testing requires a lot of soil samples and soil sampling is a time consuming, laborious process and expensive process. Most of the consultants employing site specific techniques use ATVs to get around large fields when sampling. The development of an autonomous guidance system for an ATV to perform soil sampling would be greatly beneficial to them. Labor costs would be significantly reduced and the operators would be subjected to fewer environmental elements. The use of ATVs ensures that no extra capital is needed to buy a vehicle. The use of a small vehicle like an ATV also causes less soil compaction. A WAAS enabled Differential GPS with accuracies to within 9.84 feet was used as the position sensor. Pocket PCs are more portable than a laptop computer and are more suitable for farm conditions. Shape files were used to provide the sampling points as input to the guidance program. A guidance program was made to operate on a PDA and provide guidance instructions. A microprocessor was programmed to read the guidance instructions and actuate the different components like throttle and steering. Tests were conducted to test the accuracy and consistency of the system. The offsets of each stop point from the test point were documented and analyzed. The results indicated that the system was as accurate as the GPS used for guidance. They also indicated that a guidance system can be realized with the use of very few components and an accuracy needed for soil sampling can be achieved. Avoidance routines for obstacles within the field were indicated as future developments

Utilizing Repeated GPS Surveys from Field Operations for Development of Agricultural Field DEMs

Topographic data collected using RTK-DGPS-equipped farm vehicles during field operations could addadditional benefits to the original capital investment in the equipment through the development of high-accuracy field DEMs. Repeated surveys of elevation data from field operations may improve DEM accuracy over time. However, minimizing the amount of data to be processed and stored is also an important goal for practical implementation. A method was developed to utilize repeated GPS surveys acquired during field operations for generating field-level DEMs. Elevation measurement error was corrected through a continuity analysis. Fuzzy logic (FL) and weighted averaging (WA) methods were used to combine new surveys with past elevation estimates without requiring storage and reprocessing of past survey data. After 20 surveys were included, the DEM of the study area generated with FL and WA methods had an average root mean squared error (RMSE) of 0.08 m, which was substantially lower than the RMSE of 0.16 m associated with the DEM developed by averaging all data points in each grid. With minimum control of errors in elevation measurements, the effect of these errors can be reduced with appropriate data processing, including continuity analysis, fuzzy logic, and weighted averaging. Two years of GPS surveys of elevation data from field operations could reduce elevation error by 50% in field DEMs

Trends in Precision Agriculture

Precision agriculture is no longer a generic term defining our desire to more precisely manage equipment and agronomic inputs. As precision agriculture enters its sixteenth year, it has become an industry within itself and features a suite of hardware and software components aimed to improve efficiency in all areas of production agriculture. As we look back on the past sixteen years we can see clear innovations in precision agriculture that have helped shape the future direction of this industry. During its infant years, precision agriculture was focused on methods to collect production data across the field using newly available GPS technology. This was mainly focused on yield monitoring and grid soil sampling to better understand trends and management zones. During the mid to late 1990\u27s precision agriculture shifted focus towards machine control products for variable rate fertilizer placement and steering assistance, including lightbars and autosteering. The past five years have brought on another precision agriculture revolution focused on automating sections of our implements and requiring ever increasing accuracy from our GPS receivers