SafeDrones: Real-Time Reliability Evaluation of UAVs using Executable Digital Dependable Identities
Aslansefat, Koorosh, Nikolaou, Panagiota, Walker, Martin, Akram, Mohammed Naveed, Sorokos, Ioannis, Reich, Jan, Kolios, Panayiotis, Michael, Maria K., Theocharides, Theocharis, Ellinas, Georgios, Schneider, Daniel, Papadopoulos, Yiannis
–arXiv.org Artificial Intelligence
The use of Unmanned Arial Vehicles (UAVs) offers many advantages across a variety of applications. However, safety assurance is a key barrier to widespread usage, especially given the unpredictable operational and environmental factors experienced by UAVs, which are hard to capture solely at design-time. This paper proposes a new reliability modeling approach called SafeDrones to help address this issue by enabling runtime reliability and risk assessment of UAVs. It is a prototype instantiation of the Executable Digital Dependable Identity (EDDI) concept, which aims to create a model-based solution for real-time, data-driven dependability assurance for multi-robot systems. By providing real-time reliability estimates, SafeDrones allows UAVs to update their missions accordingly in an adaptive manner.
arXiv.org Artificial Intelligence
Jul-12-2022
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