2 1/2 D Visual Servoing with Respect to Unknown Objects Through a New Estimation Scheme of Camera Displacement

Classical visual servoing techniques need a strong a priori knowledge of the shape and the dimensions of the observed objects. In this paper, we present how the 2 1/2 D visual servoing scheme we have recently developed, can be used with unknown objects characterized by a set of points. Our scheme is based on the estimation of the camera displacement from two views, given by the current and desired images. Since vision-based robotics tasks generally necessitate to be performed at video rate, we focus only on linear algorithms. Classical linear methods are based on the computation of the essential matrix. In this paper, we propose a different method, based on the estimation of the homography matrix related to a virtual plane attached to the object. We show that our method provides a more stable estimation when the epipolar geometry degenerates. This is particularly important in visual servoing to obtain a stable control law, especially near the convergence of the system. Finally, experimental results confirm the improvement in the stability, robustness, and behaviour of our scheme with respect to classical methods.     

Visual servo control. I. Basic approaches

This paper 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 this paper, 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     

Robust image-based visual servoing using invariant visual information

This paper deals with the use of invariant visual features for visual servoing. New features are proposed to control the 6 degrees of freedom of a robotic system with better linearizing properties and robustness to noise than the state of the art in image-based visual servoing. We show in this paper that by using these features the behavior of image-based visual servoing in task space can be significantly improved. Several experimental results are provided and validate our proposal.     

Active vision for complete scene reconstruction and exploration

Deals with the 3D structure estimation and exploration of static scenes using active vision. Our method is based on the structure from controlled motion approach that constrains camera motions to obtain an optimal estimation of the 3D structure of a geometrical primitive. Since this approach involves gazing on the considered primitive, we have developed perceptual strategies able to perform a succession of robust estimations. This leads to a gaze planning strategy that mainly uses a representation of known and unknown areas as a basis for selecting viewpoints. This approach ensures a reconstruction as complete as possible of the scene     

Study on a cobalt silica catalyst during reduction and Fischer–Tropsch reaction: In situ EXAFS compared to XPS and XRD

The reduction of a 25 wt% Co/SiO₂ catalyst for the hydrocarbon synthesis has been followed by several techniques: XRD, TPR, XPS and in situ EXAFS. Before reduction the cobalt is present as a Co₃O₄ spinel phase. A two-step reduction of Co₃O₄ to CoO and then to Co° is observed by EXAFS. This is consistent with XPS (surface) and TPR or XRD (bulk) studies. During CO/H₂ reaction, cobalt is always in the metallic state (EXAFS). The coordination number of cobalt has been determined at each reduction step and during CO hydrogenation reaction.     

Higher alcohol and paraffin synthesis on cobalt based catalysts: Comparison of mechanistic aspects

Syngas reaction mechanism studies on cobalt based catalysts suggested that the CO dissociation step and the (alcohol and/or hydrocarbon) chain growth can be well mimicked by CO disproportionation and temperature programmed desorption (TPD) of acetaldehyde. Correlation between C₂₊ hydrocarbon selectivity and CO disproportionation on the one hand, C₂₊ alcohol selectivity and TPD after acetaldehyde adsorption on the other hand could be evidenced.     

Visual Servoing Based on Structure From Controlled Motion or on Robust Statistics

This paper focuses on the way to achieve accurate visual servoing tasks when the shape of the object being observed as well as the desired image are unknown. More precisely, we want to control the camera orientation with respect to the tangent plane at a certain object point corresponding to the center of a region of interest. We also want to observe this point at the principal point to fulfil a fixation task. A 3-D reconstruction phase must, therefore, be performed during the camera motion. Our approach is then close to the structure-from-motion problem. The reconstruction phase is based on the measurement of the 2-D motion in a region of interest and on the measurement of the camera velocity. Since the 2-D motion depends on the shape of the objects being observed, we introduce a unified motion model to cope both with planar and nonplanar objects. However, since this model is only an approximation, we propose two approaches to enlarge its domain of validity. The first is based on active vision, coupled with a 3-D reconstruction based on a continuous approach, and the second is based on statistical techniques of robust estimation, coupled with a 3-D reconstruction based on a discrete approach. Theoretical and experimental results compare both approaches.     

Catadioptric Visual Servoing From 3-D Straight Lines

In this paper, we consider the problem of controlling a 6 DOF holonomic robot and a nonholonomic mobile robot from the projection of 3-D straight lines in the image plane of central catadioptric systems. A generic central catadioptric interaction matrix for the projection of 3-D straight lines is derived using an unifying imaging model valid for an entire class of cameras. This result is exploited to design an image-based control law that allows us to control the 6 DOF of a robotic arm. Then, the projected lines are exploited to control a nonholonomic robot. We show that as when considering a robotic arm, the control objectives are mainly based on catadioptric image feature and that local asymptotic convergence is guaranteed. Simulation results and real experiments with a 6 DOF eye-to-hand system and a mobile robot illustrate the control strategy.