In this work, we investigate the impact of the wind in a drone-based delivery system. For the first time, to the best of our knowledge, we adapt the trajectory of the drone to the wind. We consider a truck-drone tandem delivery system. The drone actively reacts to the wind adopting the "most tailwind " trajectory available between the truck's path and the delivery. The truck moves on a predefined route and carries the drone close to the delivery point. We propose the (MDP) which aims, when the wind affects the delivery area, at planning minimum-energy trajectories for the drone to serve the customers starting from and returning to the truck. We then propose two algorithms that optimally solve under two different routes of the truck. We also analytically study the feasibility of sending drones with limited battery to deliver packages. Finally, we first numerically compare our algorithms on randomly generated synthetic and real data, and then we evaluate our model simulating the drone's flight in the simulator.
How the Wind Can Be Leveraged for Saving Energy in a Truck-Drone Delivery System / Sorbelli, FB; Corò, F; Palazzetti, L; Pinotti, CM; Rigoni, G. - In: IEEE TRANSACTIONS ON INTELLIGENT TRANSPORTATION SYSTEMS. - ISSN 1524-9050. - ELETTRONICO. - 24:(2023), pp. 4038-4049. [10.1109/TITS.2023.3234627]
How the Wind Can Be Leveraged for Saving Energy in a Truck-Drone Delivery System
Palazzetti, L
;Rigoni, G
2023
Abstract
In this work, we investigate the impact of the wind in a drone-based delivery system. For the first time, to the best of our knowledge, we adapt the trajectory of the drone to the wind. We consider a truck-drone tandem delivery system. The drone actively reacts to the wind adopting the "most tailwind " trajectory available between the truck's path and the delivery. The truck moves on a predefined route and carries the drone close to the delivery point. We propose the (MDP) which aims, when the wind affects the delivery area, at planning minimum-energy trajectories for the drone to serve the customers starting from and returning to the truck. We then propose two algorithms that optimally solve under two different routes of the truck. We also analytically study the feasibility of sending drones with limited battery to deliver packages. Finally, we first numerically compare our algorithms on randomly generated synthetic and real data, and then we evaluate our model simulating the drone's flight in the simulator.File | Dimensione | Formato | |
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T_ITS_2022___Extension_DCOSS___feasibility.pdf
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