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Communication-aware trajectory generation for unmanned aerial vehicles (UAVs) operating in urban environments requires simultaneous consideration of vehicle dynamics, wireless communication quality, obstacle avoidance, and onboard energy…

To meet the requirements for managing unauthorized UAVs in the low-altitude economy, a multi-modal UAV trajectory prediction method based on the fusion of LiDAR and millimeter-wave radar information is proposed. A deep fusion network for…

Unmanned Aerial Vehicles (UAVs) have become widely used in various fields and industrial applications thanks to their low operational cost, compact size and wide accessibility. However, the noise generated by drone propellers has emerged as…

In recent times, an increasing number of researchers have been devoted to utilizing deep neural networks for end-to-end flight navigation. This approach has gained traction due to its ability to bridge the gap between perception and…

Unmanned Aerial vehicles (UAVs) are widely used as network processors in mobile networks, but more recently, UAVs have been used in Mobile Edge Computing as mobile servers. However, there are significant challenges to use UAVs in complex…

Unmanned aerial vehicles (UAVs) are a relatively new technology. Their application can often involve complex and unseen problems. For instance, they can work in a cooperative-based environment under the supervision of a ground station to…

Unmanned Aerial Vehicles (UAVs) are suited as cost-effective and adaptable platforms for carrying Wi-Fi Access Points (APs) and cellular Base Stations (BSs). Implementing aerial networks in disaster management scenarios and crowded areas…

A major challenge with off-road autonomous navigation is the lack of maps or road markings that can be used to plan a path for autonomous robots. Classical path planning methods mostly assume a perfectly known environment without accounting…

We present a solution to the problem of fairly planning a fleet of Unmanned Aerial Vehicles (UAVs) that have different missions and operators, such that no one operator unfairly gets to finish its missions early at the expense of others -…

Urban air mobility (UAM) has the potential to revolutionize our daily transportation, offering rapid and efficient deliveries of passengers and cargo between dedicated locations within and around the urban environment. Before the…

Cellular networks are promising to support effective wireless communications for unmanned aerial vehicles (UAVs), which will help to enable various long-range UAV applications. However, these networks are optimized for terrestrial users,…

Low-altitude urban flight planning for small Unmanned Aircraft Systems (UAS) requires accurate vehicle, environment maps, and risk models to assure flight plans consider the urban landscape as well as airspace constraints. This paper…

Small Unmanned Aircraft Systems (sUAS) will be an important component of the smart city and intelligent transportation environments of the near future. The demand for sUAS related applications, such as commercial delivery and land…

The detection of unmanned aerial vehicles (UAVs) is important for the protection of civilian and military infrastructure. In this paper we propose a cost effective UAV detection system using sound signals obtained from microphones. The…

Air travel is one of the fastest growing modes of transportation, however, the effects of aircraft noise on populations surrounding airports is hindering its growth. In an effort to study and ultimately mitigate the impact that this noise…

Unmanned Aerial Vehicle (UAV) Vision-and-Language Navigation (VLN) is vital for applications such as disaster response, logistics delivery, and urban inspection. However, existing methods often struggle with insufficient multimodal fusion,…

Electric vertical takeoff and landing (eVTOL) aircraft operating in high-density urban airspace must maintain safe separation through tactical conflict resolution, yet the energy cost of such maneuvers has not been systematically…

Unmanned aerial vehicles combined with computer vision systems, such as convolutional neural networks, offer a flexible and affordable solution for terrain monitoring, mapping, and detection tasks. However, a key challenge remains the…

Unlike traditional multi-agent coordination frameworks, which assume a fixed number of agents, UAS traffic management (UTM) requires a platform that enables Uncrewed Aerial Systems (UAS) to freely enter or exit constrained low-altitude…

In this paper, a novel machine learning (ML) framework is proposed for enabling a predictive, efficient deployment of unmanned aerial vehicles (UAVs), acting as aerial base stations (BSs), to provide on-demand wireless service to cellular…