Related papers: Energy-Predictive Planning for Optimizing Drone Se…
Aerial drones offer a distinct potential to reduce the delivery time and energy consumption for the delivery of time-sensitive and small products. However, there is still a need in the relevant industry to understand the performance of…
This paper presents a new approach for formulating the delivery problem by drones with general energy consumption models where the drones visit a set of places to deliver parcels to customers. Drones can perform multiple trips that start…
This paper studies high-speed online planning in dynamic environments. The problem requires finding time-optimal trajectories that conform to system dynamics, meeting computational constraints for real-time adaptation, and accounting for…
In modern networks, the use of drones as mobile base stations (MBSs) has been discussed for coverage flexibility. However, the realization of drone-based networks raises several issues. One of the critical issues is drones are extremely…
Accurate navigation is of paramount importance to ensure flight safety and efficiency for autonomous drones. Recent research starts to use Deep Neural Networks to enhance drone navigation given their remarkable predictive capability for…
Drones have been considered as an alternative means of package delivery to reduce the delivery cost and time. Due to the battery limitations, the drones are best suited for last-mile delivery, i.e., the delivery from the package…
Creating an appropriate energy consumption prediction model is becoming an important topic for drone-related research in the literature. However, a general consensus on the energy consumption model is yet to be reached at present. As a…
Increasing the fuel economy of hybrid electric vehicles (HEVs) and extended range electric vehicles (EREVs) through optimization-based energy management strategies (EMS) has been an active research area in transportation. However, it is…
Obstacle avoidance path planning for uncrewed aerial vehicles (UAVs), or drones, is rarely addressed in most flight path planning schemes, despite obstacles being a realistic condition. Obstacle avoidance can also be energy-intensive,…
We propose a novel top-k service composition framework for drone services under a dynamic environment. We develop a system model for formal modelling of drone services in a skyway network. The composition process is accomplished in two…
We propose a novel resilient drone service composition framework for delivery in dynamic weather conditions. We use a skyline approach to select an optimal set of candidate drone services at the source node in a skyway network. Drone…
Joint parcel delivery by trucks and drones has enjoyed significant attention for some time, as the advantages of one delivery method offset the disadvantages of the other. This paper focuses on the vehicle routing problem with drones and…
The coordination among drones and ground vehicles for last-mile delivery has gained significant interest in recent years. In this paper, we study \textit{multiple drone delivery scheduling problem(MDSP) \cite{Betti_ICDCN22} for last-mile…
We propose a novel framework for the allocation of drone swarms for delivery services known as Swarm-based Drone-as-a-Service (SDaaS). The allocation framework ensures minimum cost (aka maximum profit) to drone swarm providers while meeting…
High-tech giants and start-ups are investing in drone technologies to provide urban air delivery service, which is expected to solve the last-mile problem and mitigate road traffic congestion. However, air delivery service will not scale up…
Smart City applications, such as traffic monitoring and disaster response, often use swarms of intelligent and cooperative drones to efficiently collect sensor data over different areas of interest and time spans. However, when the required…
In this paper, we present a drone-based delivery system that assumes to deal with two different mixed-areas, i.e., rural and urban. In these mixed-areas, called EM-grids, the distances are measured with two different metrics, and the…
This paper presents a data-driven supervisory energy management strategy (EMS) for plug-in hybrid electric vehicles which leverages Vehicle-to-Cloud connectivity to increase energy efficiency by learning control policies from completed…
The idea of deploying electric vehicles and unmanned aerial vehicles (UAVs), also known as drones, to perform "last-mile" delivery in logistics operations has attracted increasing attention in the past few years. In this paper, we propose…
Drones have a fairly short range due to their limited battery life. We propose an adaptive exploration techniques to extend the range of drones by taking advantage of physical structures such as tall buildings and trees in urban…