Abstract
AbstractCritical infrastructure protection has a significant role in the modern world. The critical infrastructure can be found in many fields, but the roads and road infrastructure surely are one of the very important factors in this domain. This paper targets the issue of utilization of Unmanned Aerial Vehicles (UAVs) for road infrastructure monitoring. The contribution of this paper is the methodology proposed for UAV path planning in urban and suburban scenarios. The purpose of UAVs is the city road condition monitoring, and the proposed methodology tends to optimize this process by usage of a minimal number of UAVs to monitor a maximal number of locations, by randomly chosen locations, and dynamically calculated paths. The methodology uses Traveling salesman Problem (TSP) with Genetic Algorithm (GA) support. The TSP solution gives the shortest direct path between randomly selected locations. To enable the following of the road TSP is expanded with Dijkstra’s shortest path algorithm giving, as a result, the calculated path which follows the city roads. The addition of Dijkstra’s shortest path algorithm does not significantly increase the length of the path, comparing to TSP calculated path.KeywordsUAV road infrastructure monitoringUAV critical infrastructure monitoringUAV path planningTravelling salesman problemDijkstra’s shortest path algorithm
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