SafeDrones: Real-Time Reliability Evaluation of UAVs using Executable Digital Dependable Identities

TL;DR

SafeDrones introduces a real-time reliability assessment method for UAVs, enabling adaptive mission updates to improve safety and dependability in unpredictable operational environments.

Contribution

It presents a novel reliability modeling approach based on Executable Digital Dependable Identities for real-time UAV dependability assessment.

Findings

Enables real-time UAV reliability estimation

Supports adaptive mission management

Addresses operational unpredictability

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.