Automatic Flight Plan Generation for UAV-Assisted Elevated Meter Reading using Ant Colony Optimization

Abstract

This paper presents the development of an Ant Colony Optimization (ACO)-based UAV flight plan generator for Automatic Electric Meter Reading (AMR) at elevated metering centers (EMC). The program's flight plan against a UAV human operator flight plans were compared for different missions and considering the following: coordinate location of EMCs, the number of electric meters within the EMC, the UAV's takeoff and landing location, the EMC's height, the UAV's position relative to the EMC during data collection, and the UAV's battery capacity. The generated flight plan captures the most EMC data in the shortest time possible, automatically. Tests conducted include the Shortest Route Test and the Largest Amount of Data per Unit Time test that compared the program's and human operator's flight plan development and mission completion times. Results revealed that the program's flight plan is 30.58 percent more efficient than the UAV human operator's during the Shortest Route Test and 28.10 percent more efficient during the Largest Amount of Data per Unit Time test.