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• W4293812084 abstract "We propose a novel framework for swarm-based drone delivery services with in-flight energy recharging. The framework aims to enhance the delivery time of multiple packages by reducing the number of stops and recharging times at intermediate stations. The proposed framework considers various <italic xmlns:mml=http://www.w3.org/1998/Math/MathML xmlns:xlink=http://www.w3.org/1999/xlink>intrinsic and extrinsic</i> delivery constraints. We propose to use <italic xmlns:mml=http://www.w3.org/1998/Math/MathML xmlns:xlink=http://www.w3.org/1999/xlink>support drones</i> whose sole purpose is to recharge other drones in the swarm during their flight. In this respect, we compute the optimal set of optimal support drones to minimize the probability of delivery services and recharging time at the next stations. We also use two settings to position the support drones in a flight formation for comparative purposes. Two novel <italic xmlns:mml=http://www.w3.org/1998/Math/MathML xmlns:xlink=http://www.w3.org/1999/xlink>energy sharing</i> methods are proposed, namely, Priority-based and Fairness-based methods. A re-ordering method of the delivery drones is presented to facilitate the in-flight energy composition process. An enhanced A* algorithm is implemented to compose the optimal services in terms of delivery time. Experimental results prove the efficiency of our proposed approach." @default.
• W4293812084 created "2022-08-31" @default.
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• W4293812084 date "2022-01-01" @default.
• W4293812084 modified "2023-10-06" @default.
• W4293812084 title "In-Flight Energy-Driven Composition of Drone Swarm Services" @default.
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• W4293812084 doi "https://doi.org/10.1109/tsc.2022.3203033" @default.
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