@misc{Nattke, author = {Nattke, Matthias}, title = {Effizientere Fl{\"a}chennutzung in der Landwirtschaft durch vernetzte Drohnen}, series = {Lecture Notes in Informatics (LNI) - Proceedings}, volume = {2021}, journal = {Lecture Notes in Informatics (LNI) - Proceedings}, number = {314}, publisher = {Springer}, address = {Berlin}, isbn = {978-3-88579-708-1}, issn = {1617-5468}, doi = {10.18420/informatik2021-032}, pages = {389 -- 400}, abstract = {Dieses Paper besch{\"a}ftigt sich mit der Frage, wie im Schwarm vernetzte Drohnen zur nachhaltigen Nutzung von landwirtschaftlichen Fl{\"a}chen beitragen k{\"o}nnen. Dazu wird auf die Vorteile und h{\"o}here Krisenresistenz regionaler Lieferketten bei Grundnahrungsmitteln hingewiesen. Als Resultat wird aufgezeigt, wie vernetzte vernetzte Drohnen zur gezielten Beobachtung von vorhanden Fl{\"a}chen eingesetzt werden k{\"o}nnen. Sie lassen sich pr{\"a}ziser und nachhaltiger bewirtschaften. Die Betrachtung umfasst technische Herausforderungen bei der Vernetzung und und dem Schwarmflug. Weitere Verbesserungsm{\"o}glichkeiten durch l{\"a}ngere Akkulaufzeiten und bessere Sensoren werden vorgeschlagen. Ein Anwendungsszenario in der Lausitz wird aufgezeigt. Im Ausblick wird die Integration in neuartige Bearbeitungsmethoden der Pr{\"a}zisionslandwirtschaft thematisiert.}, language = {de} } @misc{Nattke, author = {Nattke, Matthias}, title = {Hardware-in-the-Loop-Simulation for Collision Avoidance in Drone Swarms}, series = {NWC 2021 : NAFEMS World Congress : 25-29 October, online : incorporating SPDM, International Conference Simulation Process \& Data Management; Multiphysics Simulation Conference; CAE in automotive development: state of the art, technology changes, \& future trends : summary of proceedings}, journal = {NWC 2021 : NAFEMS World Congress : 25-29 October, online : incorporating SPDM, International Conference Simulation Process \& Data Management; Multiphysics Simulation Conference; CAE in automotive development: state of the art, technology changes, \& future trends : summary of proceedings}, isbn = {978-1-83979-212-0}, abstract = {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.}, language = {en} } @misc{NattkeRottaNatarovetal., author = {Nattke, Matthias and Rotta, Randolf and Natarov, Roman and Archila, Oscar and Mykytyn, Pavlo}, title = {Precise sensors for localization in the drone swarm}, series = {Proceedings iCCC2024 - iCampµs Cottbus Conference, 2024-05-14 - 2024-05-16, Cottbus}, volume = {2024}, journal = {Proceedings iCCC2024 - iCampµs Cottbus Conference, 2024-05-14 - 2024-05-16, Cottbus}, publisher = {AMA}, isbn = {978-3-910600-00-3}, doi = {10.5162/iCCC2024/P16}, pages = {166 -- 169}, abstract = {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.}, language = {en} } @misc{ShahinRottaArchilaetal., author = {Shahin, Keyvan and Rotta, Randolf and Archila, Oscar and Mykytyn, Pavlo and Nattke, Matthias and Reichenbach, Marc and Nolte, J{\"o}rg and Natarov, Roman}, title = {A Modular Communication Architecture for Adaptive UAV Swarms}, series = {2023 IEEE International Conference on Omni-layer Intelligent Systems (COINS)}, journal = {2023 IEEE International Conference on Omni-layer Intelligent Systems (COINS)}, publisher = {IEEE}, address = {Berlin}, isbn = {979-8-3503-4647-3}, doi = {10.1109/COINS57856.2023.10189245}, pages = {6}, abstract = {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.}, language = {en} }