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Flight Tour Planning with Recharging Optimization for Battery-operated Autonomous Drones

Abstract

Autonomous drones (also known as unmanned aerial vehicles) have several advantages over ground vehicles, including agility, swiftness, and energy-efficiency, and hence are convenient for light-weight delivery and substitutions for manned missions in remote operations. It is expected that autonomous drones will be deployed in diverse applications in near future. Typical drones are electric vehicles, powered by on-board batteries. This paper presents several contributions for automated battery-operated drone management systems: (1) We conduct an empirical study to model the battery performance of drones, considering various flight scenarios. (2) We study a joint problem of flight tour planning with recharging optimization for drones with an objective to complete a tour mission for a set of sites of interest. This problem captures diverse applications of delivery and remote operations by drones. (3) We implemented our optimization algorithms in an intelligent drone management system.

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