Image based visual servoing using algebraic curves applied to shape alignment

Visual servoing schemes generally employ various image features (points, lines, moments etc.) in their control formulation. This paper presents a novel method for using boundary information in visual servoing. Object boundaries are modeled by algebraic equations and decomposed as a unique sum of product of lines. We propose that these lines can be used to extract useful features for visual servoing purposes. In this paper, intersection of these lines are used as point features in visual servoing. Simulations are performed with a 6 DOF Puma 560 robot using Matlab Robotics Toolbox for the alignment of a free-form object. Also, experiments are realized with a 2 DOF SCARA direct drive robot. Both simulation and experimental results are quite promising and show potential of our new method

Exploring Convolutional Networks for End-to-End Visual Servoing

Present image based visual servoing approaches rely on extracting hand crafted visual features from an image. Choosing the right set of features is important as it directly affects the performance of any approach. Motivated by recent breakthroughs in performance of data driven methods on recognition and localization tasks, we aim to learn visual feature representations suitable for servoing tasks in unstructured and unknown environments. In this paper, we present an end-to-end learning based approach for visual servoing in diverse scenes where the knowledge of camera parameters and scene geometry is not available a priori. This is achieved by training a convolutional neural network over color images with synchronised camera poses. Through experiments performed in simulation and on a quadrotor, we demonstrate the efficacy and robustness of our approach for a wide range of camera poses in both indoor as well as outdoor environments.Comment: IEEE ICRA 201

Model-based vs. model-free visual servoing: A Performance evaluation in microsystems

In this paper, model-based and model-free image based visual servoing (VS) approaches are implemented on a microassembly workstation, and their regulation and tracking performances are evaluated. A precise image based VS relies on computation of the image jacobian. In the model-based visual servoing, the image Jacobian is computed via calibrating the optical system. Precisely calibrated model based VS promises better positioning and tracking performance than the model-free approach. However, in the model-free approach, optical system calibration is not required due to the dynamic Jacobian estimation, thus it has the advantage of adapting to the different operating modes

Positioning and trajectory following tasks in microsystems using model free visual servoing

In this paper, we explore model free visual servoing algorithms by experimentally evaluating their performances for various tasks performed on a microassembly workstation developed in our lab. Model free or so called uncalibrated visual servoing does not need the system calibration (microscope-camera-micromanipulator) and the model of the observed scene. It is robust to parameter changes and disturbances. We tested its performance in point-to-point positioning and various trajectory following tasks. Experimental results validate the utility of model free visual servoing in microassembly tasks

Visual Servoing from Deep Neural Networks

We present a deep neural network-based method to perform high-precision, robust and real-time 6 DOF visual servoing. The paper describes how to create a dataset simulating various perturbations (occlusions and lighting conditions) from a single real-world image of the scene. A convolutional neural network is fine-tuned using this dataset to estimate the relative pose between two images of the same scene. The output of the network is then employed in a visual servoing control scheme. The method converges robustly even in difficult real-world settings with strong lighting variations and occlusions.A positioning error of less than one millimeter is obtained in experiments with a 6 DOF robot.Comment: fixed authors lis

Visual servoing of nonholonomic cart

This paper presents a visual feedback control scheme for a nonholonomic cart without capabilities for dead reckoning. A camera is mounted on the cart and it observes cues attached on the environment. The dynamics of the cart are transformed into a coordinate system in the image plane. An image-based controller which linearizes the dynamics is proposed. Since the positions of the cues in the image plane are controlled directly, possibility of missing cues is reduced considerably. Simulations are carried out to evaluate the validity of the proposed scheme. Experiments on a radio controlled car with a CCD camera are also given</p

Image based visual servoing using bitangent points applied to planar shape alignment

We present visual servoing strategies based on bitangents for aligning planar shapes. In order to acquire bitangents we use convex-hull of a curve. Bitangent points are employed in the construction of a feature vector to be used in visual control. Experimental results obtained on a 7 DOF Mitsubishi PA10 robot, verifies the proposed method

Depth adaptive zooming visual servoing for a robot with a zooming camera

To solve the view visibility problem and keep the observed object in the field of view (FOV) during the visual servoing, a depth adaptive zooming visual servoing strategy for a manipulator robot with a zooming camera is proposed. Firstly, a zoom control mechanism is introduced into the robot visual servoing system. It can dynamically adjust the camera's field of view to keep all the feature points on the object in the field of view of the camera and get high object local resolution at the end of visual servoing. Secondly, an invariant visual servoing method is employed to control the robot to the desired position under the changing intrinsic parameters of the camera. Finally, a nonlinear depth adaptive estimation scheme in the invariant space using Lyapunov stability theory is proposed to estimate adaptively the depth of the image features on the object. Three kinds of robot 4DOF visual positioning simulation experiments are conducted. The simulation experiment results show that the proposed approach has higher positioning precision. © 2013 Xin et al