A trajectory tracking and 3D positioning controller for the AR.Drone quadrotor

Author

Vago Santana, Lucas ; Brandao, Alexandre Santos ; Sarcinelli-Filho, Mario ; Carelli, Ricardo

Author_Institution

Dept. of Ind. Autom., Fed. Inst. of Espirito Santo, Linhares, Brazil

fYear

2014

fDate

27-30 May 2014

Firstpage

756

Lastpage

767

Abstract

In this paper a complete framework is proposed, to deal with trajectory tracking and positioning with an AR.Drone Parrot quadrotor flying in indoor environments. The system runs in a centralized way, in a computer installed in a ground station, and is based on two main structures, namely a Kalman Filter (KF) to track the 3D position of the vehicle and a nonlinear controller to guide it in the accomplishment of its flight missions. The KF is designed aiming at estimating the states of the vehicle, fusing inertial and visual data. The nonlinear controller is designed with basis on a dynamic model of the AR.Drone, with the closed-loop stability proven using the theory of Lyapunov. Finally, experimental results are presented, which demonstrate the effectiveness of the proposed framework.

Keywords

Kalman filters; Lyapunov methods; autonomous aerial vehicles; closed loop systems; control engineering computing; control system synthesis; helicopters; mobile robots; nonlinear control systems; sensor fusion; stability; trajectory control; 3D positioning controller; AR.Drone Parrot quadrotor; AR.Drone dynamic model; KF; Kalman Filter; Lyapunov theory; closed-loop stability; flight missions; inertial data fusion; nonlinear controller design; trajectory tracking controller; visual data fusion; Kalman filters; Mathematical model; Sensors; State estimation; Vehicle dynamics; Visualization;

fLanguage

English

Publisher

ieee

Conference_Titel

Unmanned Aircraft Systems (ICUAS), 2014 International Conference on

Conference_Location

Orlando, FL

Type

conf

DOI

10.1109/ICUAS.2014.6842321

Filename

6842321