4.6 Article

Migratory Unmanned Aerial Vehicle System (MiUAV) for Automated Infrastructure Inspection

期刊

IEEE ACCESS
卷 11, 期 -, 页码 56392-56399

出版社

IEEE-INST ELECTRICAL ELECTRONICS ENGINEERS INC
DOI: 10.1109/ACCESS.2023.3282995

关键词

UAV; infrastructure inspection; route decision algorithm; Dijkstra

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This paper proposes a migratory UAV (MiUAV) system that enables UAVs to automatically reach infrastructure facilities, allowing pilots to conduct inspections remotely and significantly improving inspection efficiency. The proposed system includes multiple ports for accommodating and charging UAVs, and UAVs can travel between these ports to reach remote infrastructure. The route decision scheme autonomously sets a route for each UAV based on weights considering port utilization ratio and inclement weather probability, resulting in reduced travel time by avoiding high-utilization ports and bad weather areas, as shown by computer simulations.
Many infrastructure facilities such as bridges, communication towers, and power transmission lines were constructed more than 30 years ago, and their inspection work is significant for disaster prevention and mitigation. Infrastructure inspections using unmanned aerial vehicles (UAVs) have been introduced and are expected to improve inspection efficiency significantly. However, infrastructure facilities are located in various places, and the cost of dispatching pilots and UAVs to each infrastructure is increasing costs. This paper proposes a migratory UAV (MiUAV) system in which a UAV automatically moves to infrastructure facilities and a pilot inspects remotely. The proposed MiUAV consists of multiple ports that can accommodate and charge UAVs, and the UAVs can travel to remote infrastructure by flying between the ports. Assuming an environment where multiple UAVs move simultaneously, setting up a route through a port with high utilization or a bad weather area will increase the travel time to the destination. The proposed route decision scheme uses weights considering port utilization ratio and inclement weather probability and autonomously sets a route to the destination for each UAV using the Dijkstra method. Computer simulations evaluate that the proposed scheme can reduce travel time by avoiding high-utilization ports and bad weather areas.

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