scholarly journals Towards Real-time, On-board, Hardware-supported Sensor and Software Health Management for Unmanned Aerial Systems

Author(s):  
Johann Schumann ◽  
Kristin Y. Rozier ◽  
Thomas Reinbacher ◽  
Ole J. Mengshoel ◽  
Timmy Mbaya ◽  
...  

For unmanned aerial systems (UAS) to be successfully deployed and integrated within the national airspace, it is imperative that they possess the capability to effectively complete their missions without compromising the safety of other aircraft, as well as persons and property on the ground. This necessity creates a natural requirement for UAS that can respondto uncertain environmental conditions and emergent failures in real-time, with robustness and resilience close enough to those of manned systems. We introduce a system that meets this requirement with the design of a real-time onboard system health management (SHM) capability to continuously monitor sensors, software, and hardware components. This system can detect and diagnose failures and violations of safety or performance rules during the flight of a UAS. Our approach to SHM is three-pronged, providing: (1) real-time monitoring of sensor and software signals; (2) signal analysis, preprocessing, and advanced on-the-fly temporal and Bayesian probabilistic fault diagnosis; and (3) an unobtrusive, lightweight, read-only, low-power realization using Field Programmable Gate Arrays (FPGAs) that avoids overburdening limited computing resources or costly re-certification of flight software. We call this approach rt-R2U2, a name derived from its requirements. Our implementation provides a novel approach of combining modular building blocks, integrating responsive runtime monitoring of temporal logic system safety requirements with model-based diagnosis and Bayesian network-based probabilistic analysis. We demonstrate this approach using actual flight data from theNASA Swift UAS.

2007 ◽  
Vol 16 (06) ◽  
pp. 997-1010
Author(s):  
AHMED A. ELFARAG ◽  
HATEM M. El-BOGHDADI ◽  
SAMIR I. SHAHEEN

Partially reconfigurable field-programmable gate arrays (FPGAs) allow parts of the chip to be configured at runtime where each part could hold an independent task. Online placement of these tasks result in area fragmentation leading to poor utilization of chip resources. In this paper, we propose a new metric for measuring area fragmentation. The new fragmentation metric gives an indication to the continuity of the occupied (or free) space and not the amount of occupied space. We show how this metric can be extended for multidimensional structures. We also show how this metric can be computed efficiently at runtime. Next, we use this measure during online placement of tasks on FPGAs, such that the chip fragmentation is reduced. Our results show improvement of chip utilization when using this fragmentation aware placement method over other placement methods with well-known bottom left, first fit, and best-fit placement strategies. In real-time environment, we achieve an improvement in miss ratio when using the fragmentation-aware placement over the bottom left placement strategy.


2019 ◽  
Vol 146 (4) ◽  
pp. 2879-2879
Author(s):  
Ross K. Snider ◽  
Trevor Vannoy ◽  
James Eaton ◽  
Matthew Blunt ◽  
E. Bailey Galacci ◽  
...  

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