Mobile Robots Navigation

Mobile robots navigation includes different interrelated activities: (i) perception, as obtaining and interpreting sensory information; (ii) exploration, as the strategy that guides the robot to select the next direction to go; (iii) mapping, involving the construction of a spatial representation by using the sensory information perceived; (iv) localization, as the strategy to estimate the robot position within the spatial map; (v) path planning, as the strategy to find a path towards a goal location being optimal or not; and (vi) path execution, where motor actions are determined and adapted to environmental changes. The book addresses those activities by integrating results from the research work of several authors all over the world. Research cases are documented in 32 chapters organized within 7 categories next described

Sustainable Agriculture and Advances of Remote Sensing (Volume 1)

Agriculture, as the main source of alimentation and the most important economic activity globally, is being affected by the impacts of climate change. To maintain and increase our global food system production, to reduce biodiversity loss and preserve our natural ecosystem, new practices and technologies are required. This book focuses on the latest advances in remote sensing technology and agricultural engineering leading to the sustainable agriculture practices. Earth observation data, in situ and proxy-remote sensing data are the main source of information for monitoring and analyzing agriculture activities. Particular attention is given to earth observation satellites and the Internet of Things for data collection, to multispectral and hyperspectral data analysis using machine learning and deep learning, to WebGIS and the Internet of Things for sharing and publishing the results, among others

Proceedings of the European Conference on Agricultural Engineering AgEng2021

This proceedings book results from the AgEng2021 Agricultural Engineering Conference under auspices of the European Society of Agricultural Engineers, held in an online format based on the University of Évora, Portugal, from 4 to 8 July 2021. This book contains the full papers of a selection of abstracts that were the base for the oral presentations and posters presented at the conference. Presentations were distributed in eleven thematic areas: Artificial Intelligence, data processing and management; Automation, robotics and sensor technology; Circular Economy; Education and Rural development; Energy and bioenergy; Integrated and sustainable Farming systems; New application technologies and mechanisation; Post-harvest technologies; Smart farming / Precision agriculture; Soil, land and water engineering; Sustainable production in Farm buildings

Agricultural Structures and Mechanization

In our globalized world, the need to produce quality and safe food has increased exponentially in recent decades to meet the growing demands of the world population. This expectation is being met by acting at multiple levels, but mainly through the introduction of new technologies in the agricultural and agri-food sectors. In this context, agricultural, livestock, agro-industrial buildings, and agrarian infrastructure are being built on the basis of a sophisticated design that integrates environmental, landscape, and occupational safety, new construction materials, new facilities, and mechanization with state-of-the-art automatic systems, using calculation models and computer programs. It is necessary to promote research and dissemination of results in the field of mechanization and agricultural structures, specifically with regard to farm building and rural landscape, land and water use and environment, power and machinery, information systems and precision farming, processing and post-harvest technology and logistics, energy and non-food production technology, systems engineering and management, and fruit and vegetable cultivation systems. This Special Issue focuses on the role that mechanization and agricultural structures play in the production of high-quality food and continuously over time. For this reason, it publishes highly interdisciplinary quality studies from disparate research fields including agriculture, engineering design, calculation and modeling, landscaping, environmentalism, and even ergonomics and occupational risk prevention

Advanced Sensors for Real-Time Monitoring Applications

It is impossible to imagine the modern world without sensors, or without real-time information about almost everything—from local temperature to material composition and health parameters. We sense, measure, and process data and act accordingly all the time. In fact, real-time monitoring and information is key to a successful business, an assistant in life-saving decisions that healthcare professionals make, and a tool in research that could revolutionize the future. To ensure that sensors address the rapidly developing needs of various areas of our lives and activities, scientists, researchers, manufacturers, and end-users have established an efficient dialogue so that the newest technological achievements in all aspects of real-time sensing can be implemented for the benefit of the wider community. This book documents some of the results of such a dialogue and reports on advances in sensors and sensor systems for existing and emerging real-time monitoring applications

In-Soil Measuring of Sugar Beet Yield Using UWB Radar Sensor System

Yield mapping is a basic entity of the Precision Farming concept and provides crucial information about the success of cultivation. Several approaches to site-specific yield recording during the sugar beet harvest are known. Most of them are based on the weighing of sugar beets together with soil tare. Another real-time yield mapping approach with the option of plant population counting is based on estimating the mass of individual sugar beets on the basis of their maximal diameter. The main goal of the research was to develop and evaluate a yield recording procedure based on radar technology, which will provide non-invasive in-soil detection and identification of single sugar beets in order to enable the counting of individual sugar beets and determining of the single sugar beet root mass. Further goals were to enhance the radar technology for other applications in the agriculture, as a general goal, and to define applicability restrictions of practical utilisation of the system for the sugar beet and similar crops. The research activities have been divided into laboratory and field experiments. The results of the laboratory experiments have provided valuable information about the measuring system’s behaviour, which enabled the successful field measurements. The used method allowed the identification and detection of 90% to 96% of sugar beets under test in the various field conditions, with correlation coefficients between real sugar beet positions and detected positions of about 99%, and average positioning error from 1,1 to 3,6 cm. The correlation coefficients between single sugar beet root masses and recorded reflected energy amounts were for the majority of tests over 70%, and the best results have been on the level close to 90%. This project was a joint venture of the Institute for Agricultural Engineering from Bonn and the Technical University of Ilmenau.Teilflächenspezifische Ertragsmessung von Zuckerrüben im Boden mittels UWB Radarsensorsystem Die Ertragskartierung ist ein wesentlicher Bestandteil des Konzeptes „Precision Farming“. Die Erntemasse von Kulturpflanzen ist für den Landwirt eine elementare Information über den Erfolg pflanzbaulicher Maßnahmen. Es sind mehrere Verfahren zur Ertragsermittlung von Zuckerrüben während der Ernte mit dem Bezug auf Teilflächen bekannt. Ein sensorischer Ansatz besteht in der Pflanzenzählung und Ermittlung der Masse der einzelnen Zuckerrüben über den maximalen Durchmesser. Das Hauptziel dieser Forschungsarbeiten war die Entwicklung und Bewertung eines berührungslosen Ertragserfassungssystems für Zuckerrüben, das teilflächenbasiert eine Zählung und Massebestimmung der Einzelrüben ermöglicht. Die weiteren Ziele bestanden in der Weiterentwicklung der Radartechnologie für andere Einsatzgebiete der Landwirtschaft und in der Bestimmung der Anwendbarkeitsgrenzen des Systems für Zuckerrüben und ähnliche Wurzelfrüchte. Die Forschungsaktivitäten fanden im Labor und unter Feldbedingungen auf Versuchsparzellen eines typischen Zuckerrübenstandortes statt. Die Ergebnisse unter Laborbedingungen lieferten wertvolle Informationen, die erfolgreiche Feldmessungen ermöglicht haben. Die angewendete Methode hat in unterschiedlichen Messbedingungen eine 90% bis 96% erfolgreiche Zuckerrübenidentifikation ermöglicht, mit Korrelationskoeffizienten zwischen tatsächlichen und detektierten Zuckerrübenpositionen von um 99% und einem durchschnittlichen Positionierungsfehler von 1,1 bis 3,6 cm. Die Korrelationskoeffizienten zwischen der Einzelrübenmasse und der gemessenen reflektierten Energiemenge lagen im Bereich von über 70% und die besten Ergebnisse erreichten Werte von 90%. Das Projekt wurde in der Zusammenarbeit des Instituts für Landtechnik Bonn und des Instituts für Kommunikations- und Messtechnik der Technischen Universität Ilmenau durchgeführt

Filling the sensor gap: applying UAS technology to land-use research

Collecting data at ground level typically yields the most detailed information on a subject, however it is limited by the spatial extent that can be covered within a specific timeframe. Remote sensing from an aerial platform increases this spatial extent and the deployment of unmanned aircraft systems (UAS) can provide this ability directly to researchers at an affordable cost and at data resolutions that are very applicable for site specific surveys. Further to this, developments in photogrammetry software allow the creation of orthorectified spectral and structural data that can that can be classified via pixel or object-based analysis methods and applied to a wide variety of different land-use research areas. In this study a sensor package was created consisting of two off the shelf digital cameras, one un-modified and the other modified to be sensitive to near infra-red wavelengths of light. A multi-rotor aerial platform utilising an open source autopilot was assembled to enable data collection and a processing pipeline was devised to transform RAW camera imagery into georeferenced and orthorectified data, using computer vision software following the structure from motion (SfM) approach. This remote sensing tool was applied to a variety of land-use research study sites in central Scotland and Northern England with two main areas focused on. (1) The use of spectral and structural data for the detection of disease within a potato (Solanum tuberosum L.) crop revealed that UAS could be an effective tool for mapping the distribution of diseased plants. (2) Comparisons between aerial data and traditional manual assessments of a trial crop of potatoes revealed that the earliest stages of plant emergence could not be detected but later plant counts, and ground cover estimates correlated well, indicating that UAS could be an effective trials monitoring tool, giving extra structural data and potentially a more representative measure of canopy ground cover compared to traditional manual techniques. This study also showed results from experimental applications investigating the mapping of invasive non-native species and ways of enabling upscaling of greenhouse gas emissions from different land use types. Therefore, this study demonstrates that UAS equipped with basic imaging technology can be of use to a variety of land-use research areas and look set to become an invaluable remote sensing tool, which will improve further with the addition of calibrated multi-spectral sensor payloads, high precision global navigation satellite systems and relaxation in regulations governing their use