Visual Servoing Control Law Research Articles

A Direct Visual Servoing Scheme for Automatic Nanopositioning

This paper demonstrates an accurate nanopositioning scheme based on a direct visual servoing process. This technique uses only the pure image signal (photometric information) to design the visual servoing control law. With respect to traditional visual servoing approaches that use geometric visual features (points, lines ...), the visual features used in the control law is the pixel intensity. The proposed approach has been tested in term of accuracy and robustness in several experimental conditions. The obtained results have demonstrated a good behavior of the control law and very good positioning accuracy. The obtained accuracies are 89 nm, 14 nm, and 0.001 <sup xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">°</sup> in the <i xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">x</i> -, <i xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">y</i> -, and θ-axes of a positioning platform, respectively.

Robustness of Image-Based Visual Servoing With a Calibrated Camera in the Presence of Uncertainties in the Three-Dimensional Structure

This paper concerns the stability analysis of image-based visual servoing control laws with respect to uncertainties on the 3-D parameters needed to compute the interaction matrix for any calibrated central catadioptric camera. In the recent past, research on image-based visual servoing has been concentrated on potential problems of stability and on robustness with respect to camera-calibration errors. Only little attention, if any, has been devoted to the robustness of image-based visual servoing to estimation errors on the 3-D structure. It is generally believed that a rough approximation of the 3-D structure is sufficient to ensure the stability of the control law. In this paper, we prove that this is not always true and that an extreme care must be taken when approximating the depth distribution to ensure stability of the image-based control law. The theoretical results are obtained not only for conventional pinhole cameras but for the entire class of central catadioptric systems as well.

Robotic execution of everyday tasks by means of external vision/force control

In this article, we present an integrated manipulation framework for a service robot, that allows to interact with articulated objects at home environments through the coupling of vision and force modalities. We consider a robot which is observing simultaneously his hand and the object to manipulate, by using an external camera (i.e. robot head). Task-oriented grasping algorithms (Proc of IEEE Int Conf on robotics and automation, pp 1794–1799, 2007) are used in order to plan a suitable grasp on the object according to the task to perform. A new vision/force coupling approach (Int Conf on advanced robotics, 2007), based on external control, is used in order to, first, guide the robot hand towards the grasp position and, second, perform the task taking into account external forces. The coupling between these two complementary sensor modalities provides the robot with robustness against uncertainties in models and positioning. A position-based visual servoing control law has been designed in order to continuously align the robot hand with respect to the object that is being manipulated, independently of camera position. This allows to freely move the camera while the task is being executed and makes this approach amenable to be integrated in current humanoid robots without the need of hand-eye calibration. Experimental results on a real robot interacting with different kind of doors are presented.

A UAV for bridge inspection: Visual servoing control law with orientation limits

This paper describes the dynamics of an unmanned aerial vehicle (UAV) for monitoring of structures and maintenance of bridges. It presents a novel control law based on computer vision for quasi-stationary flights above a planar target. The first part of the UAV's mission is the navigation from an initial position to a final position in an unknown 3D environment. The new control law uses the homography matrix computed from the information obtained from the vision system. The control scheme will be derived with backstepping techniques. In order to keep the camera's field of view, the control law uses saturation functions for bounding the UAV orientation and limiting it to very small values.

A general approach for sensibility analysis in visual servoing

In an experimental robotic context, it is very important to study the robustness of visual servoing control laws with respect to uncertainties that arise on the camera intrinsic and extrinsic parameters. Here we propose a general approach allowing us to analyze the sensibility of such control laws with respect to the camera parameter uncertainties. We only focus on sensibility aspects and do not address the stability analysis problem. The presented approach is validated on several examples which consider uncertainties on focal length, camera optical centers and measurement noise.

Measurement errors in visual servoing

This paper addresses the issue of measurement errors in visual servoing. The error characteristics of the vision based state estimation and the associated uncertainty of the control are investigated. The major contribution is the analysis of the propagation of image error through pose estimation and visual servoing control law. Using the analysis, two classical visual servoing methods are evaluated: position-based and 2.5D visual servoing. The evaluation offers a tool to build and analyze hybrid control systems such as switching or partitioning control.

A UAV for bridge's inspection: visual servoing control law with orientation limits

This paper describes the dynamics of an Unmanned Aerial Vehicle (UAV) for monitoring of structures and maintenance of bridges. It presents a novel control law based on computer vision for quasi-stationary flights above a planar target. The first part of the UAV's mission is the navigation from an initial position to a final position in an unknown 3D environment. The new control law uses the homography matrix computed from the information coming from the vision system. It will be derived with backstepping techniques. In order to keep the target in the camera's field of view, the control law uses saturation functions for bounding the UAV orientation and limiting it to very small values.

Observability of Depth Estimation for a Hand‐Eye Robot System

ABSTRACTThis paper deals with the depth observability problem of a hand‐eye robot system. In contrast to earlier works, this paper presents a complete study of this observability problem. The velocity of the active camera in the hand‐eye robot system is considered as the input. The observability of depth estimation is then related to the velocity of the camera. A necessary and sufficient condition for the types of camera velocities necessary to ensure observability is found. This compensates for the results of earlier works, in which the velocity of camera was estimated. The theory is also verified by both simulations and experiments in this paper. Furthermore, a modified LQ visual servo control law is proposed to vary the weighting matrices so that depth estimation is improved while the level of control performance is still retained.