TY - GEN A1 - Nattke, Matthias A1 - Rotta, Randolf A1 - Natarov, Roman A1 - Archila, Oscar A1 - Mykytyn, Pavlo T1 - Precise sensors for localization in the drone swarm T2 - Proceedings iCCC2024 - iCampµs Cottbus Conference, 2024-05-14 - 2024-05-16, Cottbus N2 - 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. KW - ROS KW - GNSS KW - UWB KW - communication hub KW - UAV swarm Y1 - 2024 UR - https://www.ama-science.org/proceedings/details/4724 SN - 978-3-910600-00-3 U6 - https://doi.org/10.5162/iCCC2024/P16 VL - 2024 SP - 166 EP - 169 PB - AMA ER - TY - GEN A1 - Shahin, Keyvan A1 - Rotta, Randolf A1 - Archila, Oscar A1 - Mykytyn, Pavlo A1 - Nattke, Matthias A1 - Reichenbach, Marc A1 - Nolte, Jörg A1 - Natarov, Roman T1 - A Modular Communication Architecture for Adaptive UAV Swarms T2 - 2023 IEEE International Conference on Omni-layer Intelligent Systems (COINS) N2 - 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. Y1 - 2023 SN - 979-8-3503-4647-3 SN - 979-8-3503-4648-0 U6 - https://doi.org/10.1109/COINS57856.2023.10189245 PB - IEEE CY - Berlin ER - TY - GEN A1 - Archila, Oscar F. A1 - Wouwer, Alain Vande A1 - Schiffer, Johannes T1 - A multiple artificial potential functions approach for collision avoidance in UAV systems T2 - IEEE transactions on intelligent transportation systems N2 - Collision avoidance is a problem largely studied in robotics, particularly in uncrewed aerial vehicle (UAV) applications. The main challenges in this area are hardware limitations, the need for rapid response, and the uncertainty associated with obstacle detection. Artificial potential functions (APOFs) are a prominent method to address these challenges. However, existing solutions lack assurances regarding closed-loop stability and may result in chattering effects. Hence, we propose a high-level control method for static obstacle avoidance based on multiple artificial potential functions (MAPOFs), with a set of switching rules with conditions on the parameter tuning ensuring the stability of the final position. The stability proof is established by analyzing the closed-loop system using tools from hybrid systems theory. Furthermore, we validate the performance of the MAPOF control through simulations and real-life experiments, showcasing its effectiveness in avoiding static obstacles. KW - Artificial potential functions KW - Collision avoidance KW - Switched system KW - Uncrewed aerial vehicle (UAV) Y1 - 2025 U6 - https://doi.org/10.1109/TITS.2025.3579157 SN - 1524-9050 VL - 26 IS - 10 SP - 16688 EP - 16699 PB - IEEE CY - New York, NY ER -