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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.

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This paper presents a framework to deal with outdoor navigation using an AR.Drone Parrot quadrotor. The proposed system runs in a centralized computer, the ground station, responsible for the communication with the unmanned aerial vehicle (UAV) and for synthesizing the control signals during flight missions. The outdoor navigation is performed through using a layered control architecture, where a highlevel control algorithm, designed from the kinematic differential equations describing the movement of the UAV, is used to generate reference signals for a low-level velocity controller. To feedback the controllers, the sensorial data provided by the AR.Drone onboard sensors and a GPS module are fused through a Kalman Filter, allowing getting a more reliable estimate of the UAV state. Finally, experimental results are presented, which demonstrate the effectiveness of the proposed framework.

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