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BTU
Drones can be connected as a swarm to precisely monitor large agricultural areas and manage them more sustainable. They test sensor technology in real environments and solve complex tasks faster. Key aspects include accurate localization, reliable communication, and dynamic flight control. The localization accuracy of RTK-GNSS-enabled system, which includes GPS, GLONASS, GALILEO positioning systems is compared with Ultra-Wideband (UWB) one. The UPWARDS communication hub is presented as a processing and connection point across swarm agents. This controller also incorporates collision avoidance features and testing of evasion strategies.
Small Unmanned Aerial Vehicles (UAVs) have vast application potential from industrial logistics and disaster monitoring to smart farming, for example, to create maps with Normalized Difference Vegetation Index (NDVI) cameras and AI-based image classification or the precision spot application of fertilizers. Operating multiple UAVs in parallel, including those with different specializations, enables efficient coverage of large areas. While existing research focused mainly on predefined flight formations for swarms or autonomous missions for single UAVs, the focus of this work is on multiple UAVs with individually adaptable missions. We derive communication system requirements from swarm coordination algorithms and present a respective design. The resulting modular architecture enables future research on autonomous adaptive UAV swarms and their use as flying sensor platforms.
Dieses Paper beschäftigt sich mit der Frage, wie im Schwarm vernetzte Drohnen zur nachhaltigen Nutzung von landwirtschaftlichen Flächen beitragen können. Dazu wird auf die Vorteile und höhere Krisenresistenz regionaler Lieferketten bei Grundnahrungsmitteln hingewiesen. Als Resultat wird aufgezeigt, wie vernetzte vernetzte Drohnen zur gezielten Beobachtung von vorhanden Flächen eingesetzt werden können. Sie lassen sich präziser und nachhaltiger bewirtschaften. Die Betrachtung umfasst technische Herausforderungen bei der Vernetzung und und dem Schwarmflug. Weitere Verbesserungsmöglichkeiten durch längere Akkulaufzeiten und bessere Sensoren werden vorgeschlagen. Ein Anwendungsszenario in der Lausitz wird aufgezeigt. Im Ausblick wird die Integration in neuartige Bearbeitungsmethoden der Präzisionslandwirtschaft thematisiert.
Drones can do more complex tasks by combining them to a swarm. To cartograph the quality of an agriculture area in shorter time is even possible like a multispectral recording from different perspectives for one special point. This helps to detect fawns or crop dusting in field production. Moreover, can the agriculture open the door for rapid development of flying sensor nets. Before drone flights in swarm constellation can start, the constrains security, safety and even the higher efficiency must be validated to reduce risks to a minimum. The system analysis of all components and developed algorithms with special focus on collision avoidance is needed. Hardware-in-the-Loop-Simulations (HIL) provides the possibility to connect the virtual simulation environment with real hardware components of the developed drone swarm system. Like continuous integration systems in process of software development, it is possible to run prespecified routines for typical and critical situations.
Solutions for two main challenges must be solved to prevent swarms again collisions. First area of interest is about relative localisation. Enhances with dimension of time distances and relative velocities are calculated. In combination with the motion prediction for the whole swarm and in contrast from each drone to all others within the swarm environment, curve intersection is identified.
The second area describes communication within all swarm entities. High exchange rates of calculated and measured values, position data rises the potential for precise swarm coordination. In combination with consensus algorithms failure tolerance and knowledge about neighbours, swarm features are under deployment in redundant manner.
Integrated into the HIL-System physical circumstances like very short distances, flight trajectories down to earth and high or low temperatures are simulated.
At the end each aspect of the developed swarm system is proceeded to prepare real test flights reliable.
More and more companies are trying to optimize their corporate goals through digitalization. These include large corporations, medium-sized companies, but also small businesses. Starting with a central information system, companies are networking to obtain as much information as possible and to keep processes lean in order to increase sales and profits. The complexity of an ERP system often prevents complete transparency in use due to gaps in knowledge. This makes faster, simpler solutions from the common software shelf appear more attractive and is preferred by the user. The aim of this research is to determine the factors for the use of shadow IT. Thus, connections with general information systems such as an ERP system become recognizable. The research questions which are derived from this: What types of shadow IT exist in Germany and Serbia? What are the reasons for a use and do they entail risks?
In order to be able to answer these questions, a thorough analysis of the applied software is required. In this case, this also includes an analysis from the user's point of view. These considerations are also differentiated regionally as well as content-related in the following research. Here, experts from European companies were interviewed.
By means of a survey, participants were able to explain their use of additional software. This results in interpretations regarding the use of shadow IT. There is a clear trend towards the use of certain auxiliary software. In addition to the strengths and weaknesses of the shadow IT, this work also conveys the weak points of the standardized information system, such as the ERP system and its modules.
An Approach to Automated Tacit-Knowledge Acquistion and Transformation in Manufacturing Companies
(2017)
Long product lifecycles are standard in aerospace, thus simulation data must be handled. This data is critical because it represents real value for the enterprise. Furthermore, simulation data is created in lengthy business processes and often ends in large files. This sets challenges for handling it to allow an efficient storage approach but also full traceability. This paper is an interim result of the research projects VITIV (project number: 80164702) and the ProFIT-Programme supported by the federal state of Brandenburg and the European Union.
Initially, the status quo must be analysed. Therefore, the current development processes to develop engine parts were investigated. The focus is the data created by analysts but for this task, all input data created prior must be known, handled and stored as well. Additionally, a new modular data structure is developed to fulfil the aforementioned requirements. However, two concepts for storing must be compared. The first would be to store all input files and boundary conditions separately without storing a full executable simulation file. This approach requires the functionality to automatically rebuild the executable file which takes time but provides a lean and modular storage. The other method would be to store the large runnable file and avoid protracted processes to rebuild the file. In some cases such rebuilding could last for several weeks. In this case, traceability must be secured.
Currently, not all data regarding CAE is stored in the PLM system. The reasons differ from constraints in terms of configuration of the system, as well as a lack in foresight. This means that some process actors are focussed on a fast way to store their data but do not take into consideration that these objects must be found and used for investigations in the future.
The next step will be to work on the process automation. These workflows should reduce the amount of manual user interactions, hence to speed up the processes and avoid sources of error. Furthermore, the developed method for storing the data has to reach the next level: from the secured test environment into a pre-production system.