Overview of Ardupilot Platform Capabilities for Developing Autonomous Aerial Vehicle Control Systems Resistant to Electronic Warfare
Keywords:
autonomous aerial vehicles, electronic warfare, Ardupilot, control systemsAbstract
The purpose of this work is to explore and elucidate the capabilities of the Ardupilot platform for developing robust control systems for autonomous aerial vehicles (AAVs) that are resilient to challenges posed by electronic warfare (EW). Utilizing a comprehensive analytical approach, this study examines the platform’s ability to integrate with various AAV types, its compatibility with numerous sensors, and its provision of advanced, customizable flight control algorithms. Additionally, the research delves into Ardupilot’s simulation capabilities, specifically through Software In The Loop (SITL) and Hardware In The Loop (HITL), to safely test and refine new algorithms and configurations within a controlled setting. Findings from this investigation demonstrate that Ardupilot is a highly effective tool for engineering adaptive and secure control systems. Its features support redundant control algorithms, facilitate multiple communication channels, and enable robust data encryption, thereby ensuring operational reliability and resilience against EW threats. The theoretical implications of this research underline the significance of leveraging sophisticated simulation tools and adaptive algorithms to bolster AAV resilience. The practical implications are significant, offering pathways to enhance the reliability and security of AAV systems across military, commercial, and research domains. The originality and value of this study reside in its detailed exploration of how Ardupilot can fortify AAV control systems against the complexities of modern EW. However, this research recognizes limitations, including the necessity for extensive real-world testing to corroborate simulation-based findings and the ever-evolving nature of EW tactics, which demand continuous algorithmic updates and adaptations. Future research should aim to develop more intricate adaptive algorithms and further refine simulation environments to advance the robustness of AAVs in challenging EW scenarios.
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References
ArduPilot Dev Team. (2024, January 8). ArduPilot Simulation Documentation. https://ardupilot.org/dev/docs/simulation-2.html
ArduPilot Dev Team. (2022, February 12). Plane SITL/MAV Proxy Tutorial. https://ardupilot.org/dev/docs/plane-sitlmavproxy-tutorial.html
ArduPilot Dev Team. (2024, April 4). Simulation on Hardware. https://ardupilot.org/dev/docs/sim-on-hardware.html
ArduPilot Dev Team. (2023, January 16). Using Simulation Parameters to Control the Simulation. https://ardupilot.org/dev/docs/SITL_simulation_parameters.html
ArduPilot Dev Team. (2020, June 16). X-Plane Hardware in the Loop Simulation. https://ardupilot.org/dev/docs/x-plane-hardware-in-the-loop-simulation.html
ArduPilot Dev Team. (2023, February 22). Simple Overview of ArduPilot Operation. https://ardupilot.org/copter/docs/common-basic-operation.html
ArduPilot Dev Team. (2020, August 13). Code Overview (Copter). https://ardupilot.org/dev/docs/apmcopter-code-overview.html
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Copyright (c) 2024 Олександр Таран (Автор)
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