Abstract not found

Abstract—This paper presents a visual-servoing method that is based on 2-D ultrasound (US) images. The main goal is to guide a robot actuating a 2-D US probe in order to reach a desired cross-section image of an object of interest. The method we propose allows the control of both in-plane and out-of-plane probe motions. Its feedback visual features are combinations of moments extracted from the observed image. The exact analytical form of the interaction matrix that relates the image-moments time variation to the probe velocity is developed, and six independent visual features are proposed to control the six degrees of freedom of the robot. In order to endow the system with the capability of automatically interacting with objects of unknown shape, a model-free visual servoing is developed. For that, we propose an efficient online estimation method to identify the parameters involved in the interaction matrix. Results obtained in both simulations and experiments validate the methods presented in this paper and show their robustness to different errors and perturbations, especially those inherent to the noisy US images. Index Terms—Medical robotics, model-free servoing, modeling, ultrasound (US) imaging, visual servoing.

Abstract — In this paper a generic decoupled imaged-based control scheme for calibrated cameras obeying the unified projection model is proposed. The proposed decoupled scheme is based on the surface of object projections onto the unit sphere. Such features are invariant to rotational motions. This allows the control of translational motion independently from the rotational motion. Finally, the proposed results are validated with experiments using a classical perspective camera as well as a fisheye camera mounted on a 6 dofs robot platform. I.

Abstract — In this paper a new decoupled imaged-based control scheme is proposed from projection onto a unit sphere. This control scheme is based on moment invariants to 3D rotational motion. This allows the control of translational motion independently of the rotational one. First, the analytical form of the interaction matrix related to the spherical moments is derived. It is based on the projection of a set of points onto a unit sphere. From the spherical moment, six features are presented to control the full 6 degrees of freedom. Finally, the results are validated through realistic simulation results. I.

Abstract—This paper considers the problem of positioning an eye-in-hand system so that it becomes parallel to a planar object. Our approach to this problem is based on linking to the camera a structured light emitter designed to produce a suitable set of visual features. The aim of using structured light is not only for simplifying the image processing and allowing low-textured objects to be considered, but also for producing a control scheme with nice properties like decoupling, convergence, and adequate camera trajectory. This paper focuses on an image-based approach that achieves decoupling in all the workspace, and for which the globalconvergenceisensured in perfect conditions. The behavior of the image-based approach is shown to be partially equivalent to a 3-D visual servoing scheme, but with a better robustness with respect to image noise. Concerning the robustness of the approach against calibration errors, it is demonstrated both analytically and experimentally. Index Terms—Convergence analysis, decoupled visual features, plane-to-plane task, structured light, visual servoing. I.

Abstract — In this paper, the coupling between Jacobian learning and task sequencing through the redundancy approach is studied. It is well known that visual servoing is robust to modeling errors in the jacobian matrices. This justifies why jacobian estimation does not usually degrade the system convergence. However, we show that this is not true anymore when the redundancy formalism is used. In this case the jacobian matrix is also necessary to compute projection operators for task decomposition, which is quite sensitive to errors. We show that learning improves the servoing performance, when task sequencing is used. Conversely, sequencing improves the convergence of learning, especially for tasks involving several degrees of freedom. Eye-in-hand and eye-to-hand experiments have been performed on two robots with six degrees of freedom. I.

Abstract—The paper presents a new approach to design a control law that realizes a main task with a robotic system and simultaneously takes supplementary constraints into account. Classically, this is done by using the redundancy formalism. If the main task does not constrain all the motions of the robot, a secondary task can be achieved by using only the remaining degrees of freedom (DOF). We propose a new general method that frees up some of the DOF constrained by the main task in addition of the remaining DOF. The general idea is to enable the motions produced by the secondary control law that help the main task to be completed faster. The main advantage is to enhance the performance of the secondary task by enlarging the number of available DOF. In a formal framework, a projection operator is built which ensures that the secondary control law does not delay the completion of the main task. A control law can then be easily computed from the two tasks considered. Experiments that implement and validate this approach are presented. The visual servoing framework is used to position a six-DOF robot while simultaneously avoiding occlusions and joint limits. Index Terms—Gradient projection method, redundancy, robot control, sensor-feedback control, visual servoing. I.

Abstract—This paper is concerned with improvements to visual feature modeling using a spherical projection model. Three spherical targets are considered: a sphere, a sphere marked with a tangent vector to a point on its surface, and a sphere marked with two points on its surface. A new minimal and decoupled set of visual features is proposed for each target using any central catadioptric camera. Using the proposed set for a sphere, a classical control law is proved to be globally asymptotically stable in the presence of modeling errors and locally asymptotically stable in the presence of calibration errors, considering that perspective and paracatadioptric cameras were used. Simulation and experimental results with perspective, paracatadioptric, and fish-eye cameras validate the proposed theoretical results. Index Terms—Central catadioptric systems, spherical projection, visual servoing. I.

Abstract — This paper is concerned with the use of a spherical projection model to design optimal visual features for visual servoing. Here two special targets are considered: a sphere marked with two points on its surface and a sphere marked with a tangent vector to a point on its surface. For these targets we propose a new minimal set of six visual features which can be computed on classical perspective cameras. Using the new set, a classical control method is proved to be globally stable even in the presence of modeling error. In comparison with the previous set originally proposed for the second target, the new set draws a better camera trajectory. Finally, simulation and experimental results confirm the validity of the proposed theoretical results. I.

1 column Abstract — We present and validate a framework for visual navigation with obstacle avoidance. The approach was originally designed in [1], but major improvements and real outdoor experiments are added here. Visual navigation consists of following a path, represented as an ordered set of key images, that have been acquired in a preliminary teaching phase. While following such path, the robot is able to avoid new obstacles which were not present during teaching, and which are sensed by a range scanner. We guarantee that collision avoidance and navigation are achieved simultaneously by actuating the camera pan angle, in the presence of obstacles, to maintain scene visibility as the robot circumnavigates the obstacle. The circumnavigation verse and the collision risk are estimated using a potential vector field derived from an occupancy grid. The framework can also deal with unavoidable obstacles, which make the robot decelerate and eventually stop.