Visual Servoing of a Moving Target by an Unmanned Aerial Vehicle

To track moving targets undergoing unknown translational and rotational motions, a tracking controller is developed for unmanned aerial vehicles (UAVs). The main challenges are to control both the relative position orientation between target UAV within desired values, guarantee that generated input feasible (i.e., below its motion capability). Moreover, controlled ensure always remains field of view onboard camera. These objectives were achieved by developing nonlinear-model predictive controller, in which future predicted quadratic programming (QP). Since constraints feature vector considered when solving optimal problem, inputs can be bounded remain inside image. Three simulations performed compare efficacy performance with traditional image-based visual servoing controller.