Related papers: QUADFormer: Learning-based Detection of Cyber Atta…

Object detection from images captured by Unmanned Aerial Vehicles (UAVs) is becoming increasingly useful. Despite the great success of the generic object detection methods trained on ground-to-ground images, a huge performance drop is…

In this paper, we present an adaptive framework designed for the continuous detection, identification and classification of emerging attacks in network traffic. The framework employs a transformer encoder architecture, which captures hidden…

Integration of reinforcement learning with unmanned aerial vehicles (UAVs) to achieve autonomous flight has been an active research area in recent years. An important part focuses on obstacle detection and avoidance for UAVs navigating…

Background: Cyber-attacks have evolved rapidly in recent years, many individuals and business owners have been affected by cyber-attacks in various ways. Cyber-attacks include various threats such as ransomware, malware, phishing, and…

Unmanned Aerial Vehicles (UAVs) are remote-controlled vehicles capable of flight and are present in a variety of environments from military operations to domestic enjoyment. These vehicles are great assets, but just as their pilot can…

We address one of the main challenges towards autonomous quadrotor flight in complex environments, which is flight through narrow gaps. While previous works relied on off-board localization systems or on accurate prior knowledge of the gap…

Artificial Intelligence brings innovations into the society. However, bias and unethical exist in many algorithms that make the applications less trustworthy. Threats hunting algorithms based on machine learning have shown great advantage…

Unmanned Combat Aerial Vehicle (UCAV) Within-Visual-Range (WVR) engagement, referring to a fight between two or more UCAVs at close quarters, plays a decisive role on the aerial battlefields. With the development of artificial intelligence,…

The consumer UAV (unmanned aerial vehicle) market has grown significantly over the past few years. Despite its huge potential in spurring economic growth by supporting various applications, the increase of consumer UAVs poses potential…

With quadrotor use seeing extensive growth in recent years, the autonomous control of these Unmanned Aerial Vehicles (UAVs) is an increasing relevant and intersting field. In this paper a linear state-space approach at designing a stable…

Designing robust machine learning systems remains an open problem, and there is a need for benchmark problems that cover both environmental changes and evaluation on a downstream task. In this work, we introduce AVOIDDS, a realistic object…

Unmanned Aerial Vehicles (UAVs) rely on measurements from Inertial Measurement Units (IMUs) to maintain stable flight. However, IMUs are susceptible to physical attacks, including acoustic resonant and electromagnetic interference attacks,…

The unmanned aerial vehicle (UAV) network is popular these years due to its various applications. In the UAV network, routing is significantly affected by the distributed network topology, leading to the issue that UAVs are vulnerable to…

With the rapidly growing expansion in the use of UAVs, the ability to autonomously navigate in varying environments and weather conditions remains a highly desirable but as-of-yet unsolved challenge. In this work, we use Deep Reinforcement…

With the recent developments in artificial intelligence and machine learning, anomalies in network traffic can be detected using machine learning approaches. Before the rise of machine learning, network anomalies which could imply an…

This article presents an error-state Linear Quadratic Regulator (LQR) formulation for robust trajectory tracking in quadrotor Unmanned Aerial Vehicles (UAVs). The proposed approach leverages error-state dynamics and employs exponential…

With the advent of vehicles equipped with advanced driver-assistance systems, such as adaptive cruise control (ACC) and other automated driving features, the potential for cyberattacks on these automated vehicles (AVs) has emerged. While…

This paper presents nonlinear tracking control systems for a quadrotor unmanned aerial vehicle under the influence of uncertainties. Assuming that there exist unstructured disturbances in the translational dynamics and the attitude…

3D visual perception tasks, including 3D detection and map segmentation based on multi-camera images, are essential for autonomous driving systems. In this work, we present a new framework termed BEVFormer, which learns unified BEV…

There is a space of uncertainty in the modeling of vehicular dynamics of autonomous systems due to noise in sensor readings, environmental factors or modeling errors. We present Requiem, a software-only, blackbox approach that exploits this…