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Hierarchical Observe-Orient-Decide-Act Enabled UAV Swarms in Uncertain Environments: Frameworks, Potentials, and Challenges
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DOI：10.1109/mnet.2026.3671364.png)
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Abstract
En 中文
Uncrewed aerial vehicle (UAV) swarms are increasingly explored for their potentials in various applications such as surveillance, disaster response, and military. However, UAV swarms face significant challenges of implementing effective and rapid decisions under dynamic and uncertain environments. The traditional decision-making frameworks, mainly relying on centralized control and rigid architectures, are limited by their adaptability and scalability especially in complex environments. To overcome these challenges, in this paper, we propose a hierarchical Observe-Orient-Decide-Act (H-OODA) loop based framework for the UAV swarm operation in uncertain environments, which is implemented by embedding the classical OODA loop across the cloud-edge-terminal layers, and leveraging the network function virtualization (NFV) technology to provide flexible and scalable decision-making functions. In addition, based on the proposed H-OODA framework, we joint autonomous deci-sion-making and cooperative control to enhance the adaptability and efficiency of UAV swarms. Furthermore, we present some typical case studies to verify the improvement and efficiency of the proposed framework. Finally, the potential challenges and possible directions are analyzed to provide insights for the future H-OODA enabled UAV swarms.
Keywords:
Autonomous aerial vehicles
Decision making
Real-time systems
Cloud computing
Surveillance
Resource management
Network function virtualization
Collaboration
Computer architecture
Vehicle dynamics
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