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http://dx.doi.org/10.5139/JKSAS.2020.48.6.419

A Study on the Improvement of Searching Performance of Autonomous Flight UAVs Based on Flocking Theory  

Kim, Dae Woon (Defense Agency for Technology and Quality)
Seak, Min Jun (Defense Agency for Technology and Quality)
Kim, Byoung Soo (Gyeongsang National University)
Publication Information
Journal of the Korean Society for Aeronautical & Space Sciences / v.48, no.6, 2020 , pp. 419-429 More about this Journal
Abstract
In conducting a mission to explore and track targets using a number of unmanned aerial vehicles(UAVs), performance for that mission may vary significantly depending on the operating conditions of the UAVs such as the number of operations, the altitude, and what future flight paths each aircraft decides based on its current position. However, studies on the number of operations, operating conditions, and flight patterns of unmanned aircraft in these surveillance missions are insufficient. In this study, several types of flight simulations were conducted to detect and determine targets while multiple UAVs were involved in the avoidance of collisions according to various autonomous flight algorithms based by flocking theory, and the results were presented to suggest a more efficient/effective way to control a number of UAVs in target detection missions.
Keywords
UAV; Flocking; Autonomous Flight; Target Detection; Collision Avoidance; Simulation;
Citations & Related Records
Times Cited By KSCI : 2  (Citation Analysis)
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