Generic decoupled image-based visual servoing for cameras obeying the unified projection model

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

Visual Servoing

The goal of this book is to introduce the visional application by excellent researchers in the world currently and offer the knowledge that can also be applied to another field widely. This book collects the main studies about machine vision currently in the world, and has a powerful persuasion in the applications employed in the machine vision. The contents, which demonstrate that the machine vision theory, are realized in different field. For the beginner, it is easy to understand the development in the vision servoing. For engineer, professor and researcher, they can study and learn the chapters, and then employ another application method

Modelbased Visual Servoing Grasping of Objects Moving by Newtonian Dynamics

Robot control systems are traditionally closed system. With the aid of vision, visual feedback is used to guide the robot manipulator to the target in a similar manner as humans do. This hand-to-target task is fairly easy if the target is static in Cartesian space. However, if the target is dynamics in motion, a model of this dynamical behaviour is required in order for the robot to predict or track the target trajectory and intercept the target successfully. One the necessary modeling is done, the framework becomes one of automatic control. >p In this master thesis, we present a model-based visual servoing of a six degree-of-freedom (DOF) industrial robot in the manner of computer simulation. The objective of this thesis is to manoeuvre the robot to grasp a ball moving by Newtonian dynamics in an unattended and less structured three-dimensional environment. >p Two digital cameras are used cooperatively to capture images of the ball for computer vision system to generate qualitative visual information. The accuracy of the visual information is essential to the robotic servoing control. The computer vision system detects the ball in image space, segments the ball from the background and computes the ball in image space as visual information. The visual information is used for 3D reconstruction of the ball in Cartesian space. The trajectory of the thrown ball is then modeled and predicted. Several ball grasp positions in Cartesian space are predicted as the thrown ball travelling towards the robot. At that same time, the inverse kinematics of the robot is also computed and it steers the robot to track the predicted ball grasp positions and grasp the ball when the error is small. In addition, the performance and robustness of this model-based prediction of the ball trajectory is verified with graphical analysis

Efficient and secure real-time mobile robots cooperation using visual servoing

This paper deals with the challenging problem of navigation in formation of mobiles robots fleet. For that purpose, a secure approach is used based on visual servoing to control velocities (linear and angular) of the multiple robots. To construct our system, we develop the interaction matrix which combines the moments in the image with robots velocities and we estimate the depth between each robot and the targeted object. This is done without any communication between the robots which eliminate the problem of the influence of each robot errors on the whole. For a successful visual servoing, we propose a powerful mechanism to execute safely the robots navigation, exploiting a robot accident reporting system using raspberry Pi3. In addition, in case of problem, a robot accident detection reporting system testbed is used to send an accident notification, in the form of a specifical message. Experimental results are presented using nonholonomic mobiles robots with on-board real time cameras, to show the effectiveness of the proposed method

Visual servoing with moments of SIFT features

Robotic manipulation of daily-life objects is an essential requirement in service robotic applications. In that context image based visual servoing is a means to position the end-effector in order to manipulate objects of unknown pose. This contribution proposes a 6 DOF visual servoing scheme that relies on the pixel coordinates, scale and orientation of SIFT features. The control is based on geometric moments computed over an alterable set of redundant SIFT feature correspondences between the current and the reference view. The method is generic as it does not depend on a geometric object model but automatically extracts SIFT features from images of the object. The foundation of visual servoing on generic SIFT features renders the method robust with respect to loss of redundant features caused by occlusion or changes in view point.The moment based representation establishes an approximate one-to-one relationship between visual features and degrees of motion. This property is exploited in the design of a decoupled controller that demonstrates superior performance in terms of convergence and robustness compared with an inverse image Jacobian controller. Several experiments with a robotic arm equipped with a monocular eye-in-hand camera demonstrate that the approach is efficient and reliable

Virtual Environment for Development of Visual Servoing Control Algorithms

Our problem considered was whether a virtual environment could be used for development of visual servoing control algorithms. We have used a virtual environment for the comparison of several kinds of controllers. The virtual environment is done in Java, and it consists of two industrial robots, IRB 2000 and IRB 6, a camera stereo system with two cameras mounted on the end-effector of the IRB 6, and one rolling ball and one bar. The experiment consists of tracking and grasping the ball using the different controllers. The robot IRB 2000 should grasp the rolling ball. The control of the robot is done in Matlab. We have three controllers. These controllers are function of the difference between the ball and the gripper. First, we use P-controller with a proportional gain. Second, the image-based Jacobian control is used but this controller needs an improvement because the robot tracks the ball with a little delay, then we use this controller with feedforward. The robot grasps the ball when the error between the ball and the gripper is less than one tolerance. In these two controllers, the depth is calculated with the two cameras (stereovision), therefore cameras need to be calibrated. Third, the hybrid controller is used. It is a mix of image-based and position-based controller. We use X and Y in Image space and Z in Cartesian space. Now, the 3D reconstruction is done from motion. It means we do not need calibrated cameras and the depth is calculated with adaptive control techniques. This adaptive control is used for recovering on-line the velocity of the ball. When the estimation of the ball is stable, the robot starts tracking the ball