STRATEGY FOR USING DIGITAL TWIN IN CONDITIONS OF UAV SWARM DECENTRALIZED CONTROL
DOI:
https://doi.org/10.15407/dopovidi2025.06.023Keywords:
digital twin, swarm intelligence, autonomous navigation, unmanned aerial vehicles (UAVs), decentralized controlAbstract
A strategy for using a digital twin (DT) in the tasks of autonomous navigation tasks for swarms of unmanned aerial vehicles (UAVs) controlled by artificial intelligence is proposed. In the absence of stable communication with the ground control center, effective operation of the drone swarm is possible thanks to the distribution of digital twin functions between the ground station and the UAV’s onboard AI agents. Within the structure of the autonomous artificial intelligence platform for a swarm of unmanned aerial vehicles, the DT module performs an asynchronous but strategically important function. Its main role is to prepare, analyze, and update behavioral strategies when the vehicles are not performing combat missions. At the end of the mission or at evacuation checkpoints, the information is transmitted to the ground DT. This allows for in-depth analysis, retraining of models, and updating of knowledge used in subsequent missions. During flight, the drones operate completely autonomously, using only local sensors, a cognitive core, and adaptive algorithms, and, where possible, exchange data with the ground station. The UAV interface module is responsible for data buffering, access to the latest strategies, partial scenario modeling, and asynchronous updates when conditions allow. Its presence in the structure ensures autonomous interaction with the ground twin and local support without violating the decentralized principle of swarm control. The purpose of this paper is to develop a strategy for using a digital twin in a decentralized UAV swarm control environment, where the ground infrastructure performs strategic modeling, training, and analysis functions, and onboard AI agents provide local adaptation, diagnostics, environment reconstruction, and cognitive control of drone behavior. A practical scenario for using digital twins in swarm UAV systems is presented, demonstrating their role as the strategic core of the control system.
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