SafeDrones：使用可执行数字可靠身份对无人机进行实时可靠性评估
SafeDrones: Real-Time Reliability Evaluation of UAVs using Executable Digital Dependable Identities
AI总结：
针对无人机广泛应用中的安全保障障碍，本文提出SafeDrones这一基于可执行数字可靠身份（EDDI）的新型可靠性建模方法，实现无人机运行时可靠性与风险评估，为多机器人系统提供实时数据驱动的可靠性保障并支持任务自适应更新。
摘要：
无人驾驶飞行器（UAVs）的使用在各类应用中具有诸多优势，但安全保障是其广泛应用的关键障碍，尤其是考虑到无人机在运行中面临难以仅在设计阶段捕捉的不可预测操作与环境因素。本文提出一种名为SafeDrones的新型可靠性建模方法，通过支持无人机的运行时可靠性与风险评估来解决该问题。它是可执行数字可靠身份（EDDI）概念的原型实例，该概念旨在为多机器人系统构建基于模型的实时、数据驱动的可靠性保障解决方案。通过提供实时可靠性估计，SafeDrones使无人机能够以自适应方式相应更新任务。
英文摘要：
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.
机构、总结、中文摘要均由AI分析而来，可能存在错误，请以论文正文为准。
