Homography-Based Sampled-Data Visual Servoing

Classical position-based and image-based visual servoing methods suffer from some drawbacks, the former require a three-dimensional model of the observed scene and they are sensitive to camera calibration errors, the convergence of the latter cannot be ensured in the whole feature space. In the last two decades, the homography-based visual servoing approaches have been widely investigated. They overcome the above drawbacks and avoid the intermediate process of feature extraction. The main results on homography-based control schemes are formulated in the continuous time domain. Due to the limited camera frame rate, actuation delay, and computation time, the intrinsic sampled-data nature of such control schemes should be taken into account. To this aim, in this letter, we propose an exact sampled-data model of the homography dynamics and an adaptive visual controller that directly uses the homography matrix and explicitly takes into account camera velocity limits ensuring global asymptotic stability at the same time.