Enhanced Image-Based Visual Servoing Dealing with Uncertainties

Nowadays, the applications of robots in industrial automation have been considerably increased. There is increasing demand for the dexterous and intelligent robots that can work in unstructured environment. Visual servoing has been developed to meet this need by integration of vision sensors into robotic systems. Although there has been significant development in visual servoing, there still exist some challenges in making it fully functional in the industry environment. The nonlinear nature of visual servoing and also system uncertainties are part of the problems affecting the control performance of visual servoing. The projection of 3D image to 2D image which occurs in the camera creates a source of uncertainty in the system. Another source of uncertainty lies in the camera and robot manipulator's parameters. Moreover, limited field of view (FOV) of the camera is another issues influencing the control performance. There are two main types of visual servoing: position-based and image-based. This project aims to develop a series of new methods of image-based visual servoing (IBVS) which can address the nonlinearity and uncertainty issues and improve the visual servoing performance of industrial robots. The first method is an adaptive switch IBVS controller for industrial robots in which the adaptive law deals with the uncertainties of the monocular camera in eye-in-hand configuration. The proposed switch control algorithm decouples the rotational and translational camera motions and decomposes the IBVS control into three separate stages with different gains. This method can increase the system response speed and improve the tracking performance of IBVS while dealing with camera uncertainties. The second method is an image feature reconstruction algorithm based on the Kalman filter which is proposed to handle the situation where the image features go outside the camera's FOV. The combination of the switch controller and the feature reconstruction algorithm can not only improve the system response speed and tracking performance of IBVS, but also can ensure the success of servoing in the case of the feature loss. Next, in order to deal with the external disturbance and uncertainties due to the depth of the features, the third new control method is designed to combine proportional derivative (PD) control with sliding mode control (SMC) on a 6-DOF manipulator. The properly tuned PD controller can ensure the fast tracking performance and SMC can deal with the external disturbance and depth uncertainties. In the last stage of the thesis, the fourth new semi off-line trajectory planning method is developed to perform IBVS tasks for a 6-DOF robotic manipulator system. In this method, the camera's velocity screw is parametrized using time-based profiles. The parameters of the velocity profile are then determined such that the velocity profile takes the robot to its desired position. This is done by minimizing the error between the initial and desired features. The algorithm for planning the orientation of the robot is decoupled from the position planning of the robot. This allows a convex optimization problem which lead to a faster and more efficient algorithm. The merit of the proposed method is that it respects all of the system constraints. This method also considers the limitation caused by camera's FOV. All the developed algorithms in the thesis are validated via tests on a 6-DOF Denso robot in an eye-in-hand configuration

Robust eye tracking based on multiple corneal reflections for clinical applications

Postprint (published version

On the Calibration of Active Binocular and RGBD Vision Systems for Dual-Arm Robots

This paper describes a camera and hand-eye calibration methodology for integrating an active binocular robot head within a dual-arm robot. For this purpose, we derive the forward kinematic model of our active robot head and describe our methodology for calibrating and integrating our robot head. This rigid calibration provides a closedform hand-to-eye solution. We then present an approach for updating dynamically camera external parameters for optimal 3D reconstruction that are the foundation for robotic tasks such as grasping and manipulating rigid and deformable objects. We show from experimental results that our robot head achieves an overall sub millimetre accuracy of less than 0.3 millimetres while recovering the 3D structure of a scene. In addition, we report a comparative study between current RGBD cameras and our active stereo head within two dual-arm robotic testbeds that demonstrates the accuracy and portability of our proposed methodology

Encoderless Gimbal Calibration of Dynamic Multi-Camera Clusters

Dynamic Camera Clusters (DCCs) are multi-camera systems where one or more cameras are mounted on actuated mechanisms such as a gimbal. Existing methods for DCC calibration rely on joint angle measurements to resolve the time-varying transformation between the dynamic and static camera. This information is usually provided by motor encoders, however, joint angle measurements are not always readily available on off-the-shelf mechanisms. In this paper, we present an encoderless approach for DCC calibration which simultaneously estimates the kinematic parameters of the transformation chain as well as the unknown joint angles. We also demonstrate the integration of an encoderless gimbal mechanism with a state-of-the art VIO algorithm, and show the extensions required in order to perform simultaneous online estimation of the joint angles and vehicle localization state. The proposed calibration approach is validated both in simulation and on a physical DCC composed of a 2-DOF gimbal mounted on a UAV. Finally, we show the experimental results of the calibrated mechanism integrated into the OKVIS VIO package, and demonstrate successful online joint angle estimation while maintaining localization accuracy that is comparable to a standard static multi-camera configuration.Comment: ICRA 201

On Real-Time Synthetic Primate Vision

The primate vision system exhibits numerous capabilities. Some important basic visual competencies include: 1) a consistent representation of visual space across eye movements; 2) egocentric spatial perception; 3) coordinated stereo fixation upon and pursuit of dynamic objects; and 4) attentional gaze deployment. We present a synthetic vision system that incorporates these competencies.We hypothesize that similarities between the underlying synthetic system model and that of the primate vision system elicit accordingly similar gaze behaviors. Psychophysical trials were conducted to record human gaze behavior when free-viewing a reproducible, dynamic, 3D scene. Identical trials were conducted with the synthetic system. A statistical comparison of synthetic and human gaze behavior has shown that the two are remarkably similar

Mechatronic design of the Twente humanoid head

This paper describes the mechatronic design of the Twente humanoid head, which has been realized in the purpose of having a research platform for human-machine interaction. The design features a fast, four degree of freedom neck, with long range of motion, and a vision system with three degrees of freedom, mimicking the eyes. To achieve fast target tracking, two degrees of freedom in the neck are combined in a differential drive, resulting in a low moving mass and the possibility to use powerful actuators. The performance of the neck has been optimized by minimizing backlash in the mechanisms, and using gravity compensation. The vision system is based on a saliency algorithm that uses the camera images to determine where the humanoid head should look at, i.e. the focus of attention computed according to biological studies. The motion control algorithm receives, as input, the output of the vision algorithm and controls the humanoid head to focus on and follow the target point. The control architecture exploits the redundancy of the system to show human-like motions while looking at a target. The head has a translucent plastic cover, onto which an internal LED system projects the mouth and the eyebrows, realizing human-like facial expressions

Unobtrusive and pervasive video-based eye-gaze tracking

Eye-gaze tracking has long been considered a desktop technology that finds its use inside the traditional office setting, where the operating conditions may be controlled. Nonetheless, recent advancements in mobile technology and a growing interest in capturing natural human behaviour have motivated an emerging interest in tracking eye movements within unconstrained real-life conditions, referred to as pervasive eye-gaze tracking. This critical review focuses on emerging passive and unobtrusive video-based eye-gaze tracking methods in recent literature, with the aim to identify different research avenues that are being followed in response to the challenges of pervasive eye-gaze tracking. Different eye-gaze tracking approaches are discussed in order to bring out their strengths and weaknesses, and to identify any limitations, within the context of pervasive eye-gaze tracking, that have yet to be considered by the computer vision community.peer-reviewe