Double Exponential Smoothing for predictive vision based target tracking of a wheeled mobile robot

This paper describes the design of a novel nonlinear kinematic controller which allows a wheeled mobile robot to track a moving target at a given separation distance. The Double Exponential Smoothing algorithm is employed to deal with uncertainties in the measurements and to acquire a predictive estimate for the robot´s relative position. This estimate is used to automatically adjust the proportional gain of the controller in order to regulate the tracking error.