Over the past two decades, Unmanned Aerial Vehicles (UAVs), or drones, have gained significant attention and adoption across diverse domains, including logistics, disaster response, and surveillance. Drone design is inherently multidisciplinary, requiring the integration of aerodynamics, power management, embedded software, and fault tolerance. However, current simulation frameworks typically isolate these concerns, making it difficult to analyze them and to design effective fault management strategies. This paper proposes a unified co-simulation framework that enables concurrent modeling and analysis across mechanical, electrical, software, and environmental domains. The framework integrates: (1) SystemC AMS for modeling analog/mixed-signal, electromechanical, and power subsystems; (2) an Instruction Set Simulator (ISS) for software execution and profiling; and (3) Unreal Engine for high-fidelity visualization, environmental modeling, and user interaction. The proposed integration supports holistic design space exploration and early fault injection for a preliminary evaluation of fault analysis and for the design of fault recovery mechanisms. The platform promotes a white-box approach to UAV design, providing insight into how faults propagate across subsystems and performing efficient power design space exploration.
A Multi-domain Simulation Framework for Enhanced Drone Design and Fault Management / Ni, R., Pollo, G., Tosoni, F., Fummi, F., Poncino, M., Macii, E., Burrello, A., Jahier Pagliari, D., Vinco, S.. - In: ACM TRANSACTIONS ON CYBER-PHYSICAL SYSTEMS. - ISSN 2378-962X. - ACM Transactions on Cyber-Physical Systems:(In corso di stampa).
A Multi-domain Simulation Framework for Enhanced Drone Design and Fault Management
RUICONG NI;GIOVANNI POLLO;FRANCO FUMMI;MASSIMO PONCINO;ENRICO MACII;ALESSIO BURRELLO;DANIELE JAHIER PAGLIARI;SARA VINCO
In corso di stampa
Abstract
Over the past two decades, Unmanned Aerial Vehicles (UAVs), or drones, have gained significant attention and adoption across diverse domains, including logistics, disaster response, and surveillance. Drone design is inherently multidisciplinary, requiring the integration of aerodynamics, power management, embedded software, and fault tolerance. However, current simulation frameworks typically isolate these concerns, making it difficult to analyze them and to design effective fault management strategies. This paper proposes a unified co-simulation framework that enables concurrent modeling and analysis across mechanical, electrical, software, and environmental domains. The framework integrates: (1) SystemC AMS for modeling analog/mixed-signal, electromechanical, and power subsystems; (2) an Instruction Set Simulator (ISS) for software execution and profiling; and (3) Unreal Engine for high-fidelity visualization, environmental modeling, and user interaction. The proposed integration supports holistic design space exploration and early fault injection for a preliminary evaluation of fault analysis and for the design of fault recovery mechanisms. The platform promotes a white-box approach to UAV design, providing insight into how faults propagate across subsystems and performing efficient power design space exploration.| File | Dimensione | Formato | |
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SystemC_AMS_and_Unreal_Engine_for_Electric_Multirotor_Drones_Design_and_Diagnosis (2)_compressed.pdf
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https://hdl.handle.net/11583/3017079
