@inproceedings{f8f0e79b267a4732aff622ac7034409e,
title = "Pattern Forming Acceleration for Dancing UAVs Using Ant Colony Optimization",
abstract = "A dancing UAVshow is a performance where a number of UAVs fly and form certain patterns. The dancing UAV performance is very limited by the show time and also the flying time of each UAV. Beside the time problem, determining the trajectory of each UAV to form certain patterns in a three-dimensional area is a problem. To overcome the time problem and determine the trajectory, it is necessary to determine the best waypoint and trajectory. In this paper, we use Ant Colony Optimization (ACO) as a method to figure out the best waypoint and trajectory. Experiments using simulations were carried out to see the magnitude of the effect of selecting the best waypoint and trajectory using the ACO. The results of the experiment show that method can shorten the distance, especially for the pattern that formed with the large number of UAVs.",
keywords = "ACO, UAV, optimization, pattern forming",
author = "Andri Suhartono and Ronny Mardiyanto",
note = "Publisher Copyright: {\textcopyright} 2020 IEEE.; 2020 International Seminar on Intelligent Technology and Its Application, ISITIA 2020 ; Conference date: 22-07-2020 Through 23-07-2020",
year = "2020",
month = jul,
doi = "10.1109/ISITIA49792.2020.9163718",
language = "English",
series = "Proceedings - 2020 International Seminar on Intelligent Technology and Its Application: Humanification of Reliable Intelligent Systems, ISITIA 2020",
publisher = "Institute of Electrical and Electronics Engineers Inc.",
pages = "279--284",
booktitle = "Proceedings - 2020 International Seminar on Intelligent Technology and Its Application",
address = "United States",
}