TY - GEN
T1 - A Distributed Semi-Autonomous Strategy for One-to-Many UAV Cooperative Transport Within Virtual Tubes
AU - Gu, Shuang
AU - Liu, Runxiao
AU - Gao, Yan
AU - Quan, Quan
N1 - Publisher Copyright:
© 2026 IEEE.
PY - 2026
Y1 - 2026
N2 - This paper proposes a distributed strategy for oneto-many unmanned aerial vehicle (UAV) transport, in which a single human operator can manage multiple UAVs in a semi-autonomous mode. Cooperative transport control and virtual tube passage control are integrated within the virtual system, allowing UAVs to safely get through pre-planned virtual tubes. A single human controller enters commands through the keyboard, and the router broadcasts the velocity scaling factor and desired rotation angle to all UAVs. The swarm executes keyboard commands for velocity adjustment along the tube, collective rotation, and collective return, which realize more diverse collective motion modes. Simulation with ten UAVs and outdoor experiments with three UAVs are conducted in two types of tubes: with a straight generator curve and with an irregular generator curve. The results indicate that the proposed strategy improves the consistency and adaptability of UAV swarms when unexpected situations arise.
AB - This paper proposes a distributed strategy for oneto-many unmanned aerial vehicle (UAV) transport, in which a single human operator can manage multiple UAVs in a semi-autonomous mode. Cooperative transport control and virtual tube passage control are integrated within the virtual system, allowing UAVs to safely get through pre-planned virtual tubes. A single human controller enters commands through the keyboard, and the router broadcasts the velocity scaling factor and desired rotation angle to all UAVs. The swarm executes keyboard commands for velocity adjustment along the tube, collective rotation, and collective return, which realize more diverse collective motion modes. Simulation with ten UAVs and outdoor experiments with three UAVs are conducted in two types of tubes: with a straight generator curve and with an irregular generator curve. The results indicate that the proposed strategy improves the consistency and adaptability of UAV swarms when unexpected situations arise.
UR - https://www.scopus.com/pages/publications/105047312241
U2 - 10.1109/ICCA69928.2026.11618279
DO - 10.1109/ICCA69928.2026.11618279
M3 - 会议稿件
AN - SCOPUS:105047312241
T3 - IEEE International Conference on Control and Automation, ICCA
SP - 1594
EP - 1600
BT - 2026 IEEE 20th International Conference on Control and Automation, ICCA 2026
PB - IEEE Computer Society
T2 - 20th IEEE International Conference on Control and Automation, ICCA 2026
Y2 - 16 June 2026 through 19 June 2026
ER -