TY - GEN
T1 - Implementation of Modified Ant-Colony Optimization Algorithm using Crazyflie Nano Quadcopters
AU - Priandana, Karlisa
AU - Dewi Hardhienata, Medria Kusuma
AU - Satya, Pradhipta Trimanggala
AU - Wulandari,
AU - Widhi Surya Atman, Made
N1 - Publisher Copyright:
© 2023 IEEE.
PY - 2023
Y1 - 2023
N2 - Multi-UAV systems have been widely used in various fields, including agriculture. Effective coordination and task allocation are essential components of these systems. This study focuses on optimizing the coordination of multi-UAVs by adapting Modified Ant Colony Optimization (M-ACO) and K-Means Algorithms. Prior to implementing these algorithms, it is necessary to configure a multi/swarm-UAV system. In this study, we have configured the Crazyflie UAVs and Crazyswarm software for a laboratory experiment. Subsequently, the configured swarm-UAV system undergoes testing using the M-ACO algorithm, and the results are compared with the actual positions in real experiments. The experiments revealed that the average position errors for the UAVs are as follows: -0.084 ± 0.033 cm for the x-axis, -0.251 ± 0.2 cm for the y-axis, and 0.01 ± 0.09 cm for the z-axis. These results indicate that, in general, the UAVs can achieve their target positions with a relatively low margin of error.
AB - Multi-UAV systems have been widely used in various fields, including agriculture. Effective coordination and task allocation are essential components of these systems. This study focuses on optimizing the coordination of multi-UAVs by adapting Modified Ant Colony Optimization (M-ACO) and K-Means Algorithms. Prior to implementing these algorithms, it is necessary to configure a multi/swarm-UAV system. In this study, we have configured the Crazyflie UAVs and Crazyswarm software for a laboratory experiment. Subsequently, the configured swarm-UAV system undergoes testing using the M-ACO algorithm, and the results are compared with the actual positions in real experiments. The experiments revealed that the average position errors for the UAVs are as follows: -0.084 ± 0.033 cm for the x-axis, -0.251 ± 0.2 cm for the y-axis, and 0.01 ± 0.09 cm for the z-axis. These results indicate that, in general, the UAVs can achieve their target positions with a relatively low margin of error.
KW - ACO
KW - crazyflie
KW - crazyswarm
KW - multi-uav
KW - swarmuav
U2 - 10.1109/INCITEST59455.2023.10397008
DO - 10.1109/INCITEST59455.2023.10397008
M3 - Conference contribution
AN - SCOPUS:85185199996
T3 - INCITEST 2023 - Proceedings of the 2023 International Conference on Informatics Engineering, Science and Technology
BT - INCITEST 2023 - Proceedings of the 2023 International Conference on Informatics Engineering, Science and Technology
PB - IEEE
T2 - 2023 International Conference on Informatics Engineering, Science and Technology, INCITEST 2023
Y2 - 25 October 2023
ER -