Año: 2017
Autores: Milton Cesar Paes Santos ; Rosales, C.; Sarcinelli-Filho, M.; Carelli, R.;
Resumen: A new trajectory tracking controller with collision avoidance is proposed in this paper for unmanned aerial vehicle (UAV) navigation. A positive potential function is designed to take into account the movement of obstacles. Thus, the controller with potential function guarantees that the UAV moves through areas of potentials close to zero to ensure safe navigation in dynamic and unknown environments. Such a controller was designed with hierarchical objectives using a behavioral-based approach. A nullspace-based controller is adopted, whose main objective is to ensure that the collision avoidance is achieved, whereas other objectives are projected onto the null space. Collision avoidance and trajectory tracking controllers generate reference velocities sent to a dynamic compensator to guarantee the tracking of such velocities, thus characterizing a cascade controller. Stability of the entire closed-loop nonlinear system is demonstrated through Lyapunov’s theory. A low-cost indoor framework with just one RGB-D sensor, which is a combination of a RGB (red-green-blue) camera with a depth sensor based on infrared light was used to estimate the positions of the UAV and obstacles. Simulation and experiments are run using a Parrot AR.Drone quadrotor and considering a person as a dynamic obstacle for an AR.Drone quadrotor, and some of their results are reported to validate the proposed controller.