  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 learned 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 by using simulations and
experiments with actual drones.
