Real-Time Safety Assessment of Unmanned Aircraft Systems Against Stealthy Cyber Attacks

2016 ◽  
Vol 13 (1) ◽  
pp. 27-45 ◽  
Author(s):  
Cheolhyeon Kwon ◽  
Scott Yantek ◽  
Inseok Hwang
Keyword(s):  
Real Time ◽  
Safety Assessment ◽  
Cyber Attacks ◽  
Unmanned Aircraft ◽  
Unmanned Aircraft Systems ◽  
Aircraft Systems

Real-time unmanned aircraft systems surveillance video mosaicking using GPU

2010 ◽  
Author(s):  
Aldo Camargo ◽  
Kyle Anderson ◽  
Yi Wang ◽  
Richard R. Schultz ◽  
Ronald A. Fevig
Keyword(s):  
Real Time ◽  
Unmanned Aircraft ◽  
Unmanned Aircraft Systems ◽  
Surveillance Video ◽  
Aircraft Systems

scholarly journals Virtual testbed for monocular visual navigation of small unmanned aircraft systems

2020 ◽  
pp. 154851292095454
Author(s):  
Kyung Kim ◽  
Robert C Leishman ◽  
Scott L Nykl
Keyword(s):  
Real Time ◽  
Visual Odometry ◽  
Visual Navigation ◽  
Unmanned Aircraft ◽  
Unmanned Aircraft Systems ◽  
Military Operations ◽  
Flight Tests ◽  
Aircraft Systems ◽  
Navigation Algorithms ◽  
Virtual Testbed

Monocular visual navigation methods have seen significant advances in the last decade, recently producing several real-time solutions for autonomously navigating small unmanned aircraft systems without relying on the Global Positioning System (GPS). This is critical for military operations that may involve environments where GPS signals are degraded or denied. However, testing and comparing visual navigation algorithms remains a challenge since visual data is expensive to gather. Conducting flight tests in a virtual environment is an attractive solution prior to committing to outdoor testing. This work presents a virtual testbed for conducting simulated flight tests over real-world terrain and analyzing the real-time performance of visual navigation algorithms at 31 Hz. This tool was created to ultimately find a visual odometry algorithm appropriate for further GPS-denied navigation research on fixed-wing aircraft, even though all of the algorithms were designed for other modalities. This testbed was used to evaluate three current state-of-the-art, open-source monocular visual odometry algorithms on a fixed-wing platform: Direct Sparse Odometry, Semi-Direct Visual Odometry, and ORB-SLAM2 (with loop closures disabled).

A neurobiologically-inspired intelligent trajectory tracking control for unmanned aircraft systems with uncertain system dynamics and disturbance

2018 ◽  
Vol 41 (2) ◽  
pp. 417-432 ◽  
Author(s):  
Mohammad Jafari ◽  
Hao Xu ◽  
Luis Rodolfo Garcia Carrillo
Keyword(s):  
System Dynamics ◽  
Real Time ◽  
Uncertain System ◽  
Emotional Learning ◽  
Unmanned Aircraft ◽  
Unmanned Aircraft Systems ◽  
Unmanned Aircraft System ◽  
Trajectory Tracking Control ◽  
Aircraft Systems ◽  
Aircraft System

In this paper, a novel neurobiologically-inspired intelligent tracking controller is developed and implemented for unmanned aircraft systems in the presence of uncertain system dynamics and disturbance. The methodology adopted, known as Brain Emotional Learning Based Intelligent Controller (BELBIC), is based on a novel computational model of emotional learning within brain limbic systems in mammals. Compared to conventional model-based control methods, BELBICs are more suitable for practical unmanned aircraft systems since they can maintain the real-time unmanned aircraft system performance without known system dynamics and disturbance. Furthermore, the learning capability and low computational complexity of BELBIC mean that it is very promising for implementation in complex real-time applications. Moreover, we proved that our proposed methodology guarantees convergence. To evaluate the practical performance of our proposed design, BELBIC has been implemented into a benchmark unmanned aircraft system. Numerical and experimental results demonstrated the applicability and satisfactory performance of the proposed BELBIC-inspired design.

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