TY - GEN
T1 - Brain-machine Cooperative Control for Multi-robot Formation
AU - Yang, Zhenge
AU - Bi, Luzheng
AU - Fei, Weijie
AU - Zhang, Peiyu
N1 - Publisher Copyright:
© 2024 IEEE.
PY - 2024
Y1 - 2024
N2 - With the aging of society and the growing number of patients experiencing motor dysfunction, enhancing their quality of life and autonomy has become increasingly crucial.This paper proposes a brain-computer synergistic multi-robot formation control technique aimed at efficiently managing multi-robot formations through brain-computer interface (BCI) technology.The system framework includes a Leader Controller, Follower Controller, Formation Decision Module, and Autonomous Navigation Module.Experimental validation demonstrates the system's performance in tasks such as formation transformation and autonomous navigation.Results confirm that the auxiliary controller effectively tracks user formation control intentions and accomplishes multi-robot formation tasks safely.Moreover, the autonomous navigation module significantly enhances system autonomy, reduces user control demands, and alleviates user control burdens.This research contributes to improving the quality of life for motor disorder patients by leveraging advanced BCI and robotics technologies to facilitate independent living and social participation through enhanced task assistance and reduced dependency on direct user control.
AB - With the aging of society and the growing number of patients experiencing motor dysfunction, enhancing their quality of life and autonomy has become increasingly crucial.This paper proposes a brain-computer synergistic multi-robot formation control technique aimed at efficiently managing multi-robot formations through brain-computer interface (BCI) technology.The system framework includes a Leader Controller, Follower Controller, Formation Decision Module, and Autonomous Navigation Module.Experimental validation demonstrates the system's performance in tasks such as formation transformation and autonomous navigation.Results confirm that the auxiliary controller effectively tracks user formation control intentions and accomplishes multi-robot formation tasks safely.Moreover, the autonomous navigation module significantly enhances system autonomy, reduces user control demands, and alleviates user control burdens.This research contributes to improving the quality of life for motor disorder patients by leveraging advanced BCI and robotics technologies to facilitate independent living and social participation through enhanced task assistance and reduced dependency on direct user control.
KW - Auxiliary control
KW - BCI
KW - Multi-robot formation
UR - http://www.scopus.com/inward/record.url?scp=85218001536&partnerID=8YFLogxK
U2 - 10.1109/ICUS61736.2024.10840070
DO - 10.1109/ICUS61736.2024.10840070
M3 - Conference contribution
AN - SCOPUS:85218001536
T3 - Proceedings of 2024 IEEE International Conference on Unmanned Systems, ICUS 2024
SP - 1305
EP - 1310
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 -