This article is the first of a two-part series on the topic of visual servo control—using computer vision data in the servo loop to control the motion of a robot. In the present article, we describe the basic techniques that are by now well established in the field. We first give a general overview of the formulation of the visual servo control problem. We then describe the two archetypal visual servo control schemes: image-based and position-based visual servo control. Finally, we discuss performance and stability issues that pertain to these two schemes, motivating the second article in the series, in which we consider advanced techniques.

The tracking algorithm presented in this paper is based on minimizing the sum-of-squared-difference between a given template and the current image. Theoretically, amongst all standard minimization algorithms, the Newton method has the highest local convergence rate since it is based on a second-order Taylor series of the sum-of-squareddifferences. However, the Newton method is time consuming since it needs the computation of the Hessian. In addition, if the Hessian is not positive definite, convergence problems can occur. That is why several methods use an approximation of the Hessian. The price to pay is the loss of the high convergence rate. The aim of this paper is to propose a tracking algorithm based on a second-order minimization method which does not need to compute the Hessian.

Abstract — Moments are generic (and usually intuitive) descriptors that can be computed from several kinds of objects defined either from closed contours or from a set of points. In this paper, we present improvements in image-based visual servo using image moments. First, the analytical form of the interaction matrix related to the moments computed from a set of coplanar points is derived, and we show that it is different of the form obtained previously using coplanar closed contours. Six visual features are selected to design a decoupled control scheme when the object is parallel to the image plane. This nice property is then generalized to the case where the desired object position is not parallel to the image plane. Finally, experimental results are presented to illustrate the validity of our approach and its robustness with respect to modeling errors. Index Terms — Visual servoing, image moment, invariant. I.

We propose an efficient non-parametric diffeomorphic image registration algorithm based on Thirion’s demons algorithm. In the first part of this paper, we show that Thirion’s demons algorithm can be seen as an optimization procedure on the entire space of displacement fields. We provide strong theoretical roots to the different variants of Thirion’s demons algorithm. This analysis predicts a theoretical advantage for the symmetric forces variant of the demons algorithm. We show on controlled experiments that this advantage is confirmed in practice and yields a faster convergence. In the second part of this paper, we adapt the optimization procedure underlying the demons algorithm to a space of diffeomorphic transformations. In contrast to many diffeomorphic registration algorithms, our solution is computationally efficient since in practice it only replaces an addition of displacement fields by a few compositions. Our experiments show that in addition to being diffeomorphic, our algorithm provides results that are similar to the ones from the demons algorithm but with transformations that are much smoother and closer to the gold standard, available in controlled experiments, in terms of Jacobians.

This paper proposes a new way to achieve robotic tasks by visual servoing. Instead of using geometric features (points, straight lines, pose, homography, etc.) as it is usually done, we use directly the luminance of all pixels in the image. Since most of the classical control laws fail in this case, we turn the visual servoing problem into an optimization problem leading to a new control law. Experimental results validate the proposed approach and show its robustness regarding to approximated depths, non Lambertian objects and partial occlusions.

We propose a non-parametric diffeomorphic image registration algorithm based on Thirion’s demons algorithm. The demons algorithm can be seen as an optimization procedure on the entire space of displacement fields. The main idea of our algorithm is to adapt this procedure to a space of diffeomorphic transformations. In contrast to many diffeomorphic registration algorithms, our solution is computationally efficient since in practice it only replaces an addition of free form deformations by a few compositions. Our experiments show that in addition to being diffeomorphic, our algorithm provides results that are similar to the ones from the demons algorithm but with transformations that are much smoother and closer to the true ones in terms of Jacobians.

Abstract — Robotized ultrasound examination offers on one hand more accuracy for the medical diagnostic and on the other hand a suitable assistance to radiologists. In the literature, very few researches deal with ultrasound image-based control of a medical robot holding the ultrasound probe. This paper presents a new visual servoing approach allowing the automatic guidance of the ultrasound probe. This technique is based on the modeling of the coupling between the ultrasound probe and egg shaped objects. The robotic task consists in reaching a desired image from an arbitrary initial position. The aim of this task is to assist the radiologist diagnostic by automatically moving the ultrasound probe in order to find the ultrasound image view of a tumour cross-section registered in a previous date. This work presents simulation results of the proposed ultrasound visionbased control scheme. Index Terms — Visual servoing, ultrasound images, medical robotics.

Abstract — This paper presents a new visual servoing method that is able to stabilize a moving area of soft tissue within an ultrasound B-mode imaging plane. The approach consists of moving the probe in order to minimize the relative position between a target imaging plane and the ultrasound plane observed by the probe of the moving tissue target. The problem is decoupled into motion out-of-plane and motion within plane. For the former, a new original method based on the speckle information contained in the images is developed. For the latter, an image region tracker is used to provide the in-plane motion. A visual servoing control scheme is then developed to perform the tracking robotic task. The method is validated on simulated motions of a probe on a static ultrasound volume acquired from a phantom. Index Terms — Visual servoing, ultrasound, speckle correlation, medical robotics.

Abstract — In this paper, we present a generic and flexible system for vision-based robot control. The system integrates several research areas (visual matching, visual tracking and visual servoing) in a unifying framework. In this framework, the flexibility is obtained using a template matching algorithm based on an efficient second-order minimization. Contrarily to feature-based visual servoing schemes, we avoid the design of feature-dependent visual tracking algorithms. By integrating the visual tracking process with the visual servoing techniques, we can more easily deal with constrained tasks. This reduces the computation cost and improves the precision of the system. The experimental results prove the efficiency of the unified system in real conditions. I.

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