TY - GEN
T1 - Mission Oriented Flocking and Distributed Formation Control of UAVs
AU - Sial, Muhammad Baber
AU - Wang, Shaoping
AU - Wang, Xingjian
AU - Wyrwa, Justyna
AU - Liao, Zirui
AU - Ding, Wenjie
N1 - Publisher Copyright:
© 2021 IEEE.
PY - 2021/8/1
Y1 - 2021/8/1
N2 - This paper presents the development of a novel autonomous search, detect and task execution model for Unmanned Aerial Vehicle (UAV) distributed formations. This work studies the problems of formation flocking, tracking and collision avoidance for a distributed formation of UAVs by use of multi-agent graph theory and artificial potential field approach in the first stage, based upon the proposed algorithm the second stage implements target search, detection and mission execution tasks, while the last stage carries out the re-flocking of the vacant UAVs. In order to validate the model, simulations were performed for every stage of the process to evaluate the desired flocking and task execution performance of the distributed formation. Finally, the results obtained from the simulations indicate that UAVs using the proposed model are able to execute the mission as per desired performance goals.
AB - This paper presents the development of a novel autonomous search, detect and task execution model for Unmanned Aerial Vehicle (UAV) distributed formations. This work studies the problems of formation flocking, tracking and collision avoidance for a distributed formation of UAVs by use of multi-agent graph theory and artificial potential field approach in the first stage, based upon the proposed algorithm the second stage implements target search, detection and mission execution tasks, while the last stage carries out the re-flocking of the vacant UAVs. In order to validate the model, simulations were performed for every stage of the process to evaluate the desired flocking and task execution performance of the distributed formation. Finally, the results obtained from the simulations indicate that UAVs using the proposed model are able to execute the mission as per desired performance goals.
KW - Artificial potential field
KW - Distributed formation control
KW - Formation flocking
KW - Multi-agent graph theory
KW - Swarm UAVs
KW - Unmanned Aerial Vehicles (UAVs)
UR - https://www.scopus.com/pages/publications/85115448966
U2 - 10.1109/ICIEA51954.2021.9516246
DO - 10.1109/ICIEA51954.2021.9516246
M3 - 会议稿件
AN - SCOPUS:85115448966
T3 - Proceedings of the 16th IEEE Conference on Industrial Electronics and Applications, ICIEA 2021
SP - 1507
EP - 1512
BT - Proceedings of the 16th IEEE Conference on Industrial Electronics and Applications, ICIEA 2021
PB - Institute of Electrical and Electronics Engineers Inc.
T2 - 16th IEEE Conference on Industrial Electronics and Applications, ICIEA 2021
Y2 - 1 August 2021 through 4 August 2021
ER -