Software architecture for managing a group of UAVS
DOI:
https://doi.org/10.54858/dndia.2024-20-5Keywords:
unmanned aviation, joint aviation group, decision-making algorithms, management efficiency coefficient, distributed computing and data storage, real-time data processingAbstract
The article explores the main approaches to creating a software architecture for controlling a group of unmanned aerial vehicles (UAVs) in the context of modern technological capabilities and challenges. The growing need for complex autonomous systems to perform various tasks, such as surveillance, monitoring and rescue operations, all require new approaches to controlling multiple drones, ensuring their coordination, safety and reliability. A method of coordinating actions between multiple drones is discussed in detail, which allows for more efficient information exchange and task performance in a group. In addition, considerable attention is paid to algorithms that ensure optimal communication between UAVs and help coordinate their activities to achieve a common goal. The article also emphasises the importance of reliable and secure communication between the UAV and the operator's ground centre, which is especially important for tasks that require a rapid response to changing environmental conditions. Real-time data processing approaches that rapidly increase the autonomy and flexibility of the system, allowing drones to adapt to changing conditions and make optimal decisions within their tasks. UAV group management software supports distributed information processing, which reduces the load on the central node and reduces the risk of malfunctions of individual drones.
In addition, the article outlines the prospects for integrating the proposed architecture with existing automated control system technologies. The main challenges, such as scaling systems, ensuring cybersecurity during data exchange, and developing algorithms to optimise the resources of a group of UAVs, are considered. This approach makes it possible to create efficient and reliable UAV group control software that can adapt to different operational scenarios and ensure safe task performance. Due to distributed data processing, secure communication, and integration of deep learning algorithms, the system maintains high autonomy and reliability during the mission. The article outlines the prospects and main challenges for building software that allows for effective management of a group of UAVs, including the possibility of integration with existing technologies.
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