Navigation and Cooperative Control Using the AR.Drone Quadrotor

This paper presents a computational system designed to perform autonomous indoor flights using low-cost equipment. Depending on the mission to be accomplished, one or two Parrot AR.Drone 2.0 quadrotors are supposed to fly in a three-dimensional workspace, guided by the navigation algorithms embedded in the proposed framework, which runs in a ground control computer. The tasks addressed involve positioning, trajectory tracking and leader-follower formation control. The key techniques required to solve such problems are reported in topics, including the mathematic modelling of the quadrotor, a model-based nonlinear flight controller and a state estimation strategy for sensory data fusion. The framework embeds the last two subsystems just mentioned, plus a communication link between the ground computer and the aircraft, to read the sensory data and to send the control signals necessary to guide the vehicle. Some experimental results are also presented and discussed, which allow concluding that the proposed methods are efficient in accomplishing the tasks addressed.

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