dc.contributor.author |
Ma J. |
|
dc.contributor.author |
Guo D. |
|
dc.contributor.author |
Bai Y. |
|
dc.contributor.author |
Svinin M. |
|
dc.contributor.author |
Magid E. |
|
dc.date.accessioned |
2022-02-09T20:46:15Z |
|
dc.date.available |
2022-02-09T20:46:15Z |
|
dc.date.issued |
2021 |
|
dc.identifier.uri |
https://dspace.kpfu.ru/xmlui/handle/net/170163 |
|
dc.description.abstract |
This paper presents a control strategy for caging a flood area via multiple UAVs. The strategy consists of the following parts. A novel architecture for video segmentation, Multiscale Features Fusion based MobileNet (MFFM-Net), is constructed to detect the flood boundary. A Function Approximation Technique based Immersion and Invariance (FATII) tracking controller is employed to constrain a single UAV on the flood boundary in the presence of external disturbances. A flocking based formation controller is designed to uniformly distribute UAVs along the flood boundary without collisions among neighbours. The proposed strategy has been verified through simulations under the ROS/Gazebo environment. |
|
dc.title |
A vision-based robust adaptive control for caging a flood area via multiple UAVs |
|
dc.type |
Conference Proceeding |
|
dc.collection |
Публикации сотрудников КФУ |
|
dc.relation.startpage |
386 |
|
dc.source.id |
SCOPUS-2021-SID85112460103 |
|