相关论文: Energy-Predictive Planning for Optimizing Drone Se…

We propose a novel framework for the recommendation of swarm-based drone delivery services based on the consumers preferences. We propose a density-based pruning approach that uses the concept of partnerships with charging station providers…

With the high flexibility of supporting resource-intensive and time-sensitive applications, unmanned aerial vehicle (UAV)-assisted mobile edge computing (MEC) is proposed as an innovational paradigm to support the mobile users (MUs). As a…

Unmanned Aerial Vehicles (UAVs), commonly known as drones, have experienced expanding use in urban environments in recent years. However, the growing density of drones raises significant challenges, such as avoiding collisions and managing…

Unmanned aerial vehicles, or drones, have the potential to significantly reduce the cost and time of making last-mile deliveries and responding to emergencies. Despite this potential, little work has gone into developing vehicle routing…

Unmanned aerial vehicles (UAVs), commonly known as drones, are being increasingly deployed throughout the globe as a means to streamline monitoring, inspection, mapping, and logistic routines. When dispatched on autonomous missions, drones…

Swarm of drones are increasingly being asked to carry out missions that can't be completed by one drone. Particularly, in delivery, issues arise due to the swarm's limited flight endurance. Hence, we propose a novel formation-guided…

We introduce a package service model where trucks as well as drones can deliver packages. Drones can travel on trucks or fly; but while flying, drones can only carry one package at a time and have to return to a truck to charge after each…

As Urban air mobility scales, commercial drone fleets offer a compelling, yet underexplored opportunity to function as mobile sensor networks for real-time urban traffic monitoring. In this paper, we propose a decentralized framework that…

Problem definition: Drones, despite being acknowledged as a transformative force in the city logistics sector, are unable to execute the \textit{last-meter delivery} (unloading goods directly to customers' doorsteps) due to airspace…

Rapid post-disaster road damage assessment is critical for effective emergency response, yet traditional optimization methods suffer from excessive computational time and require domain knowledge for algorithm design, making them unsuitable…

Recently, an unmanned aerial vehicle (UAV), as known as drone, has become an alternative means of package delivery. Although the drone delivery scheduling has been studied in recent years, most existing models are formulated as a single…

In this paper, we study the feasibility of sending drones to deliver goods from a depot to a customer by solving what we call the Mission-Feasibility Problem (MFP). Due to payload constraints, the drone can serve only one customer at a…

Given a fleet of drones with different speeds and a set of package delivery requests, the collaborative delivery problem asks for a schedule for the drones to collaboratively carry out all package deliveries, with the objective of…

In this paper, we present an online planning-scheduling approach for battery-powered autonomous aerial robots. The approach consists of simultaneously planning a coverage path and scheduling onboard computational tasks. We further derive a…

For the problem of delivering a package from a source node to a destination node in a graph using a set of drones, we study the setting where the movements of each drone are restricted to a certain subgraph of the given graph. We consider…

We present a novel investigation into the impact of inter-drone interference on delivery efficiencies within multi-drone skyway networks. We conduct controlled experiments to analyze the behavior of drones in an indoor testbed environment.…

Recent advancements in unmanned aerial vehicles, also known as drones, have motivated logistics to use drones for multiple operations. Collaboration between drones and trucks in a last-mile delivery system has numerous benefits and reduces…

Autonomous robots are increasingly deployed for long-term information-gathering tasks, which pose two key challenges: planning informative trajectories in environments that evolve across space and time, and ensuring persistent operation…

This note presents an analytical framework for decision-making in drone swarm systems operating under uncertainty, based on the integration of Partially Observable Markov Decision Processes (POMDP) with Deep Deterministic Policy Gradient…

This paper proposes an Emergency Battery Service (EBS) for drones in which an EBS drone flies to a drone in the field with a depleted battery and transfers a fresh battery to the exhausted drone. The authors present a unique battery…