TY - GEN
T1 - Human-Machine Cooperative Control of UAV in Complex Indoor Environments
AU - Ding, Jiawen
AU - Liu, Ying
AU - Bi, Luzheng
AU - Feleke, Aberham Genetu
AU - Fei, Weijie
N1 - Publisher Copyright:
© 2024 IEEE.
PY - 2024
Y1 - 2024
N2 - Unmanned aerial vehicle (UAV), as a current research hotspot, has a vast potential application prospect in military and civilian sectors, and it helps to deal with the coping ability of dangerous and complex scenes.Most of the UAVs based on autonomous control systems or manual control have poor adaptability to complex environments and weak anti-interference ability, which limits the application scope of UAVs.In this paper, authority allocation is applied to the control system of UAV, and the UAV system based on human-machine authority allocation is constructed by combining manual control with model predictive control (MPC).The performance of the system is verified through UAV simulation experiments.The experimental results show that human-machine collaborative control performs better than the manual control in terms of average completion time and collision rate, and the proposed system can improve the safety of the UAV control, and at the same time enhance the task completion efficiency of the UAV system.
AB - Unmanned aerial vehicle (UAV), as a current research hotspot, has a vast potential application prospect in military and civilian sectors, and it helps to deal with the coping ability of dangerous and complex scenes.Most of the UAVs based on autonomous control systems or manual control have poor adaptability to complex environments and weak anti-interference ability, which limits the application scope of UAVs.In this paper, authority allocation is applied to the control system of UAV, and the UAV system based on human-machine authority allocation is constructed by combining manual control with model predictive control (MPC).The performance of the system is verified through UAV simulation experiments.The experimental results show that human-machine collaborative control performs better than the manual control in terms of average completion time and collision rate, and the proposed system can improve the safety of the UAV control, and at the same time enhance the task completion efficiency of the UAV system.
KW - authority allocation
KW - human-machine collaboration
KW - MPC
KW - UAV
UR - http://www.scopus.com/inward/record.url?scp=85218008790&partnerID=8YFLogxK
U2 - 10.1109/ICUS61736.2024.10840135
DO - 10.1109/ICUS61736.2024.10840135
M3 - Conference contribution
AN - SCOPUS:85218008790
T3 - Proceedings of 2024 IEEE International Conference on Unmanned Systems, ICUS 2024
SP - 1722
EP - 1726
BT - Proceedings of 2024 IEEE International Conference on Unmanned Systems, ICUS 2024
A2 - Song, Rong
PB - Institute of Electrical and Electronics Engineers Inc.
T2 - 2024 IEEE International Conference on Unmanned Systems, ICUS 2024
Y2 - 18 October 2024 through 20 October 2024
ER -