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Cyberphysical architecture of autonomous unmanned aerial vehicles: decomposition objectives

Aleksey P. Golovin Maksim A. Mitrokhin
2026 · University proceedings Volga region Technical sciences · 0 citations

Abstract

Background. The rapid evolution of unmanned aerial vehicles (UAVs) from remote surveillance tools to complex autonomous cyber-physical systems necessitates systematization of their application and control architecture. The purpose of this work is to provide a comprehensive overview of the tasks solved by autonomous UAVs in civil and special spheres, and to develop a conceptual multi-level architecture that ensures the achievement of true autonomy. Materials and methods. An analysis of modern tasks of civil (infrastructure monitoring, precision agriculture, cargo delivery, cartography, search and rescue operations) and special applications (reconnaissance, electronic warfare, target designation) was conducted. Based on this analysis, a hierarchical management model is proposed, divided into five levels: strategic, tactical, operational, functional and fundamental. Results. It has been established that effective autonomy is achieved through a clear decomposition of goals into levels. The strategic level integrates UAVs into business processes, the tactical level plans and adapts routes, the operational level ensures navigation and safety, the functional level solves applied problems (image analysis, detection), and the fundamental level maintains the system’s functionality. Using a search and rescue operation as an example, we demonstrate how the interaction of layers enables the creation of complex, adaptive, and scalable system behavior. The developed multilayer architecture represents a universal framework for designing autonomous UAV systems, transforming them from simple performers into intelligent agents of cyber-physical ecosystems. Conclusions. The key finding is that complex behavior arises from the integration of relatively simple, specialized algorithms operating at different levels of abstraction. Future research focuses on the development of cross-layer protocols, artificial intelligence algorithms for tactical and strategic planning, and the creation of standardized platforms.

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