TY - JOUR
T1 - Distributed Gaussian Process Based Cooperative Visual Pursuit Control for Drone Networks
AU - Saito, Makoto
AU - Yamauchi, Junya
AU - Fujinami, Tesshu
AU - Omainska, Marco
AU - Fujita, Masayuki
N1 - Publisher Copyright:
© 2022 Elsevier B.V.. All rights reserved.
PY - 2022/9/1
Y1 - 2022/9/1
N2 - In this paper, we propose a control law for camera-equipped drone networks to pursue a target rigid body with unknown motion based on distributed Gaussian process. First, we consider the situation where each drone has its own dataset, and learns the unknown target motion in a distributed manner. Second, we propose a control law using the distributed Gaussian processes, and show that the estimation and control errors are ultimately bounded. Furthermore, the effectiveness of the proposed method is verified first in simulations and then in experiments with actual drones.
AB - In this paper, we propose a control law for camera-equipped drone networks to pursue a target rigid body with unknown motion based on distributed Gaussian process. First, we consider the situation where each drone has its own dataset, and learns the unknown target motion in a distributed manner. Second, we propose a control law using the distributed Gaussian processes, and show that the estimation and control errors are ultimately bounded. Furthermore, the effectiveness of the proposed method is verified first in simulations and then in experiments with actual drones.
KW - cooperative control
KW - distributed Gaussian process
KW - Vision-based control
UR - http://www.scopus.com/inward/record.url?scp=85145665153&partnerID=8YFLogxK
U2 - 10.1016/j.ifacol.2022.10.499
DO - 10.1016/j.ifacol.2022.10.499
M3 - 会議記事
AN - SCOPUS:85145665153
SN - 1474-6670
VL - 55
SP - 126
EP - 131
JO - IFAC Proceedings Volumes (IFAC-PapersOnline)
JF - IFAC Proceedings Volumes (IFAC-PapersOnline)
IS - 27
T2 - 9th IFAC Symposium on Mechatronic Systems, MECHATRONICS 2022
Y2 - 6 September 2022 through 9 September 2022
ER -