Abstract
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.
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Acknowledgement
This work was supported by the Secure and Safe Multi-Robot Systems (SESAME) H2020 Project under Grant Agreement 101017258, the European Union’s Horizon 2020 grant agreement No 739551 (KIOS CoE) and from the Government of the Republic of Cyprus through the Cyprus Deputy Ministry of Research, Innovation and Digital Policy.
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A Appendix
A Appendix
1.1 A.1 Proposed Fault Tree of a Generic UAV
Figure 5 illustrates the proposed Fault Tree of a generic UAV consist of nine failure categories including: I) Communication system failure, II) navigation system failure, III) Computer system failure, IV) Environment detection systems, V) Propulsion system, VI) Energy system, VII) Obstacle avoidance system, VIII) Security system, and IX) Landing system.
Proposed fault tree of a generic UAV
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Aslansefat, K. et al. (2022). SafeDrones: Real-Time Reliability Evaluation of UAVs Using Executable Digital Dependable Identities. In: Seguin, C., Zeller, M., Prosvirnova, T. (eds) Model-Based Safety and Assessment. IMBSA 2022. Lecture Notes in Computer Science, vol 13525. Springer, Cham. https://doi.org/10.1007/978-3-031-15842-1_18
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