Related papers: Advancing Operational Efficiency: Airspace Users' …
To enhance the performance of aerial-ground networks, this paper proposes an integrated sensing and communication (ISAC) framework for multi-UAV systems. In our model, ground base stations (BSs) cooperatively serve multiple unmanned aerial…
The autonomous operation of flexible-wing aircraft is technically challenging and has never been presented within literature. The lack of an exact modeling framework is due to the complex nonlinear aerodynamic relationships governed by the…
Unmanned aerial vehicle (UAV)-assisted data collection has been emerging as a prominent application due to its flexibility, mobility, and low operational cost. However, under the dynamic and uncertainty of IoT data collection and energy…
The rapid growth in terms of the availability of transportation data provides great potential for the introduction of emerging data-driven methodologies into transportation-related research and development efforts. However, advanced…
Unmanned Aerial Vehicles (UAVs) have significantly enhanced fog computing by acting as both flexible computation platforms and communication mobile relays. In this paper, we consider four important and interdependent modules: attitude…
Owing to the controlling flexibility and cost-effectiveness, fixed-wing unmanned aerial vehicles (UAVs) are expected to serve as flying base stations (BSs) in the air-ground integrated network. By exploiting the mobility of UAVs,…
Autonomy and connectivity are considered among the most promising technologies to improve safety, mobility, fuel and time consumption in transportation systems. Some of the fuel efficiency benefits of connected and automated vehicles (CAVs)…
Designing search algorithms for finding global optima is one of the most active research fields, recently. These algorithms consist of two main categories, i.e., classic mathematical and metaheuristic algorithms. This article proposes a…
In this paper, we investigate the dynamic emergence of traffic order in a distributed multi-agent system, aiming to minimize inefficiencies that stem from unnecessary structural impositions. We introduce a methodology for developing a…
Building on our previous work, this paper investigates the effectiveness of interpolating control (IC) for real-time trajectory tracking. Unlike prior studies that focused on trajectory tracking itself or UAV stabilization control in…
In this letter, we study a buffer-aided Internet of unmanned aerial vehicles (UAVs) in which a UAV performs data sensing, stores the data, and sends it to the base station (BS) in cellular networks. To minimize the overall completion time…
Autonomous Aerial Vehicle (AAV)-assisted Internet of Things (IoT) represents a collaborative architecture in which AAV allocate resources over 6G links to jointly enhance user-intent interpretation and overall network performance. Owing to…
We design and evaluate algorithms for efficient user-mobility driven macro-cell planning in cellular networks. As cellular networks embrace heterogeneous technologies (including long range 3G/4G and short range WiFi, Femto-cells, etc.),…
Moving structured data between different big data frameworks and/or data warehouses/storage systems often cause significant overhead. Most of the time more than 80\% of the total time spent in accessing data is elapsed in…
We consider a scenario where an UAV-mounted flying base station is providing data communication services to a number of radio nodes spread over the ground. We focus on the problem of resource-constrained UAV trajectory design with (i)…
Multi-object nonprehensile transportation in teleoperation demands simultaneous trajectory tracking and tray orientation control. Existing methods often struggle with model dependency, uncertain parameters, and multi-object adaptability. We…
Recent advances in sensor and mobile devices have enabled an unprecedented increase in the availability and collection of urban trajectory data, thus increasing the demand for more efficient ways to manage and analyze the data being…
Unmanned Aerial Vehicles (UAVs) are increasingly populating urban areas for delivery and surveillance purposes. In this work, we develop an optimal navigation strategy based on Deep Reinforcement Learning. The environment is represented by…
Temporal contexts among consecutive frames are far from being fully utilized in existing visual trackers. In this work, we present TCTrack, a comprehensive framework to fully exploit temporal contexts for aerial tracking. The temporal…
We address the problem of optimizing the performance of a dynamic system while satisfying hard safety constraints at all times. Implementing an optimal control solution is limited by the computational cost required to derive it in real…