Adaptive image feature prediction and control for visual tracking with a hand-eye coordinated camera

An adaptive method for visually tracking a known moving object with a single mobile camera is described. The method differs from previous methods of motion estimation in that both the camera and the object are moving. The objective is to predict the location of features of the object on the image plane based on past observations and past control inputs and then to determine an optimal control input that will move the camera so that the image features align with their desired positions. A resolved motion rate control structure is used to control the relative position and orientation between the camera and the object. A geometric model of the camera is used to determine the linear differential transformation from image features to camera position and orientation. To adjust for modeling errors and system nonlinearities, a self-tuning adaptive controller is used to update the transformation and compute the optimal control. Computer simulations were conducted to verify the performance of the adaptive feature prediction and control