D2DC: Mid-Air Drone-to-Drone Charging to Enhance Flight Endurance Archit Jaiswal, Swarup Bhunia Department of Electrical & Computer Engineering University of Florida Gainesville, FL, USA archit.jaiswal@ufl.edu Abstract—Last-mile delivery is shipping goods by ground from distribution centers to customers. It is the supply chain’s most expensive, complex, and polluting phase. Companies seeking cheaper, faster, and greener logistics are looking to Unmanned Aerial Vehicles (UAVs/drones) for solutions. Several companies aspire to develop Urban Air Mobility (UAM) networks to provide on-demand mobility using an electrical Vertical Takeoff and Landing (eVTOL) aircraft. However, like ground electric vehicles (EVs), UAVs have limited flight endurance due to onboard power constraints. The conventional approach of charging a UAV requires it to halt the flight mission and remain grounded while charging at a slow rate. As a result, UAVs often need detours toward a charging station and add a time penalty on top of the time spent recharging at a station. Such challenges make drone technology less economical and impede its wide- scale adaptation. This paper proposes a novel mid-air Drone- to-Drone (D2D) energy-sharing paradigm, a scalable and cost- effective solution to increase the overall flight endurance of a UAV swarm. This framework allows the UAVs to share charge and sustain each other based on the instructions received from a centralized controller. We introduce innovative components such as multi-level battery architecture, a mid-air energy exchange mechanism, and a cloud-based control unit. We have also developed a drone traffic simulator to evaluate the efficacy of the proposed framework in package delivery tasks. After performing a numerical analysis using the developed simulator, we observed up to 28.24% improvement in the mission success rate and up to 10% increase in the overall flight range of a UAV swarm. Index Terms—UAVs, autonomous drones, mid-air recharging, package delivery I. I NTRODUCTION In the last decade, the utilization of UAVs has gained significant momentum as they became more autonomous and reliable. Companies are looking to deploy UAV fleets to meet the demands for faster and environment-friendly logistics. The last mile delivery accounts for up to 28% of the total transport costs for many e-commerce companies [1]. According to [1], the total costs of global parcel delivery have exceeded $70 billion annually, and last-mile delivery accounts for more than 50% of these total costs. Besides logistics, eVTOL aircraft are seen as the future of UAM. NASA has at least 17 agreements with companies to evaluate the capabilities and flight service preparedness for UAM [2]. Companies are actively seeking to invest in deploying UAV fleets to enhance productivity. The aim is to maximize (a) Cloud-based control unit commands the UAV fleet. It com- prises a database, a charge sched- uler, and an optimizer. (b) Donor and Recipient drones form a pair and are aligned for on-the-go energy transfer while they both fly together. Fig. 1: Overview of a UAV swarm utilizing the D2DC frame- work operational uptime and achieve a better return on investments (ROI). However, the limited flight endurance due to onboard power constraints has been a major concern [3]. UAVs often need detours to reach a charging station, adding a time penalty on top of the time spent recharging at a station. The challenges of limited charging infrastructure and longer overall travel time make drone technology less economical and impede its wide-scale adaptation. Both EV and UAV industries are actively seeking advances in battery technology; however, its relatively slow research hinders the widespread adoption of electric-powered vehicles, especially drones. The existing proposals to solve the range anxiety problem of UAVs face several practical, economic, or scalability constraints when implementing them in real-world situations. In response to these challenges, we propose a novel Drone- to-Drone (D2D) energy-sharing paradigm to increase the flight endurance of a UAV swarm. This paper proposes a mid- air recharging framework in which a network of collabo- rative UAVs will dynamically address each other’s power requirements. Adopting this framework will reduce the need to visit charging stations, thereby increasing the overall pro- ductivity and flight endurance of a UAV swarm. We have developed a drone traffic simulator to quantitatively analyze the effectiveness of the D2DC framework and presented the results in this paper. We have also discussed the foundational assumptions behind the simulator’s architecture to provide a clear understanding of the context in which this framework is 2024 International Conference on Unmanned Aircraft Systems (ICUAS) June 4-7, 2024 | Chania, Crete, Greece 979-8-3503-5788-2/24/$31.00 ©2024 IEEE 893