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Warehouse management is a crucial task for most of nowadays' business activities. The usage of small Unmanned Aerial Vehicles (UAVs) has been recently proposed to automatize the inventory process while increasing the safety for human workers. However, the practical deployment of UAV swarms in the target use-case must face many severe technical issues, such as the indoor navigation, the package identification and the limited flight autonomy of the drones. In this challenging context, the paper addresses three novel research contributions. First, we propose a generic architecture for UAV-based inventory management within large-scale warehouses, including the components of UAV path planning, package identification (via QR Codes), data validation (via the Blockchain) and wireless charging; a prototype implementation of the data acquisition and management framework has been conducted by using low-cost mini-drones and single-board computers. Second, we analyze the system performance and specifically the trade-off between the inventory accuracy, i.e. rate of successful package identification, and the inventory completion time. Third, we derive the optimal UAV mobility parameters in terms of speed and number of visits for each shelf unit, and test the system operations and the configuration parameters through a small-case testbed.
Cristiani et al. (Sat,) studied this question.