Towards real-time, on-board, hardware-supported sensor and software health management for unmanned aerial systems

Unmanned aerial systems (UASs) can only be deployed if they can effectively complete their missions and respond to failures and uncertain environmental conditions while main-taining safety with respect to other aircraft as well as hu-mans and property on the ground. In this paper, we design a real-time, on-board system health management (SHM) ca-pability to continuously monitor sensors, software, and hard-ware components for detection and diagnosis of failures and violations of safety or performance rules during the flight of a UAS. Our approach to SHM is three-pronged, provid-ing: (1) real-time monitoring of sensor and/or software sig-nals; (2) signal analysis, preprocessing, and advanced on-the-fly temporal and Bayesian probabilistic fault diagnosis; (3) an unobtrusive, lightweight, read-only, low-power real-ization using Field Programmable Gate Arrays (FPGAs) that avoids overburdening limited computing resources or cost-ly re-certification of flight software due to instrumentation. Johann Schumann et al. This is an open-access article distributed under the terms of the Creative Commons Attribution 3.0 United States License, which permits unrestricted use, distribution, and reproduction in any medium, pro-vided the original author and source are credited. Our implementation provides a novel approach of combin-ing modular building blocks, integrating responsive runtime monitoring of temporal logic system safety requirements with model-based diagnosis and Bayesian network-based proba-bilistic analysis. We demonstrate this approach using actual data from the NASA Swift UAS, an experimental all-electric aircraft. 1