The problem of establishing if it is possible to reach the desired location keeping all features in the field of view and following a straight line is considered. The proposed approach is based on the polynomial parameterization of the camera path and allows one to find the path that follows a straight line and maximizes the distance of the image trajectories from the screen boundary.

This paper presents the Automatic Control Telelab (ACT), a remote laboratory for education in robotics and automation developed in Siena. A special attention is devoted to the new ACT process, a Lego mobile robot, which has been recently added to the telelab. Remote users can control the Lego mobile robot, and all the other processes, using an Internet browser. Moreover users can design new controllers by means of the Matlab/Simulink environment. The ACT home page is http://www.dii.unisi.it//spl sim/control/act.

A new visual servoing technique consisting of generating circular-like trajectories is proposed which does not require either geometrical models of the object or points depth. For calibrated camera, the object is kept in the field of view and global stability is achieved. Then, necessary and sufficient conditions are provided for establishing tolerable errors on the estimates of the intrinsic and extrinsic parameters in order to guarantee robust field of view and robust local stability. Simulation results show that the translational trajectories obtained in presence of large displacements are significantly shorter than those produced by one of the best existing methods, in both cases of correct and bad calibration. Very satisfactory results are obtained also in presence of small displacements.

A visual servoing strategy for keeping features in the field of view is proposed which consists of a switching among position-based control strategies and backward motion. In the absence of uncertainty on the extrinsic parameters, all features are kept in the field of view. Moreover, if the intrinsic parameters are also known, the trajectory length is minimized in the rotational space and, for some cases, also minimized in the translational space. Simulation results also show a certain degree of robustness against uncertainty on the intrinsic parameters.

The first aim of any visual-servoing strategy is to avoid features being lost from the field of view and that the desired location may not be reached. However, avoiding both these system failures turns out to be very difficult, especially when the initial and desired locations are distant. Moreover, the methods that succeed in presence of large camera displacements often produce a long translational trajectory that may not be allowed by the robot workspace and/or joint limits. In this paper, a new strategy for dealing with such problems is proposed, which consists of generating circular-like trajectories that may satisfy the task requirements more naturally than other solutions. Knowledge of geometrical models of the object or points depth is not required. It is shown that system failures are avoided for a calibrated camera. Moreover, necessary and sufficient conditions are provided for establishing tolerable errors on the estimates of the intrinsic and extrinsic parameters, in order to guarantee a robust field of view and robust local asymptotic stability. Several simulation results show that the translational trajectories obtained in presence of large displacements are significantly shorter than those produced by the existing methods, in cases of both correct and bad camera calibration. Very satisfactory results are achieved also in presence of small displacements.

In this paper, a visual servoing strategy for dealing with the problem of keeping the observed points in the camera field of view is proposed. The approach consists of a switching control law based on camera displacement estimation and regulated from the position of the points in the image. In absence of uncertainties on the intrinsic parameters and optical axis direction, global stability is achieved and all points are kept in the field of view. Moreover, the trajectory length is minimized in the rotational space and, for some cases, also minimized in the translational one. Robustness against uncertainties is also guaranteed.

Ultrasound technologies have been widely used in gynecology and obstetrics. Modern ultrasound systems allow the reconstruction of a 3D model of the subject being scanned. Even though visual interfaces have reached very high standards, the problem of representing a 3D image on a 2D computer screen still exists. Moreover, no physical interaction is possible with such model. The FeTouch system, developed at Siena University in the last two years, partially solves such issues by using stereo visual feedback and haptic devices. While the system can be used with any 3D model obtained from ultrasound scans, its current prime use is to allow mothers to interact with a model of the fetus they are carrying. The system, which is freely available on the project web page, has been tested on twelve cases which have been monitored by doctors at Siena Hospital.

The problem of simultaneous localization and map building for a team of cooperating robots moving in an unknown environment is addressed. The robots have to estimate the position of distinguishable static landmarks, and then localize themselves with respect to other robots and landmarks, exploiting distance and angle measurements. A novel set theoretic approach to this problem is presented. The proposed localization algorithm provides position estimates and guaranteed uncertainty regions for all robots and landmarks in the environment.

This paper proposes a visual servoing algorithm for hand-eye robotic system based on epipolar geometry. The control law is based on the estimation of the epipoles position obtained by points correspondences extracted from the current and target images. The camera-robot motion is computed from the observation of the epipoles coordinates. Only the principal camera point is assumed to be known but not the other intrinsic parameters. Experimental results are reported to validate the visual servoing algorithm proposed.

In this paper, a new method for the estimation of the fundamental matrix from point correspondences in stereo vision is presented. The minimization of the algebraic error is performed while taking explicitly into account the rank-two constraint on the fundamental matrix. It is shown how this nonconvex optimization problem can be solved avoiding local minima by using recently developed convexification techniques. The obtained estimate of the fundamental matrix turns out to be more accurate than the one provided by the linear criterion, where the rank constraint of the matrix is imposed after its computation by setting the smallest singular value to zero. This suggests that the proposed estimate can be used to initialize nonlinear criteria, such as the distance to epipolar lines and the gradient criterion, in order to obtain a more accurate estimate of the fundamental matrix.

A visual servoing algorithm for mobile robots is proposed. The main feature of the algorithm is that it exploits object profiles rather than solving correspondence problems using object features or texture. This property is crucial for mobile robot navigation in unstructured environments where the 3D scene exhibits only surfaces whose main features are their apparent contours. The framework is based on the epipolar geometry, which is recovered from object profiles and epipolar tangencies. Special symmetry conditions of epipoles are used to generate the mobile robot control law. For the sake of simplicity, mobile robot kinematics is assumed to be holonomic and the camera intrinsic parameters are assumed partially known. Such assumption can be relaxed to extend the application field of the approach.

This paper addresses the localization problem for a mobile robot navigating in an unstructured outdoor environment. A new technique is introduced, for computing an estimate of the position of the robot and the related uncertainty region, in the presence of visual angle measurements affected by bounded errors. The proposed set membership estimation procedure exploits the structure of the static set estimator, to solve recursively the dynamic localization problem.