Distributed Gaussian Process Based Cooperative Visual Pursuit Control for Drone Networks

Autor:	Saito, Makoto, Yamauchi, Junya, Fujinami, Tesshu, Omainska, Marco, Fujita, Masayuki
Rok vydání:	2022
Předmět:	Electrical Engineering and Systems Science - Systems and Control
Druh dokumentu:	Working Paper
Popis:	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. Comment: This work has been accepted to IFAC for publication under a Creative Commons Licence CC-BY-NC-ND
Databáze:	arXiv
Externí odkaz:	http://arxiv.org/abs/2205.13714 Zobrazit plný text záznamu View this record from Arxiv