Image Based Visual Servoing For Robotic Systems
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Image Based Visual Servoing For Robotic Systems
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Author : Warren Dixon
language : en
Publisher:
Release Date : 2004
Image Based Visual Servoing For Robotic Systems written by Warren Dixon and has been published by this book supported file pdf, txt, epub, kindle and other format this book has been release on 2004 with categories.
There is significant motivation to provide robotic systems with improved autonomy as a means to significantly accelerate deactivation and decommissioning (D & D) operations while also reducing the associated costs, removing human operators from hazardous environments, and reducing the required burden and skill of human operators. To achieve improved autonomy, this project focused on the basic science challenges leading to the development of visual servo controllers. The challenge in developing these controllers is that a camera provides 2-dimensional image information about the 3-dimensional Euclidean-space through a perspective (range dependent) projection that can be corrupted by uncertainty in the camera calibration matrix and by disturbances such as nonlinear radial distortion. Disturbances in this relationship (i.e., corruption in the sensor information) propagate erroneous information to the feedback controller of the robot, leading to potentially unpredictable task execution. This research project focused on the development of a visual servo control methodology that targets compensating for disturbances in the camera model (i.e., camera calibration and the recovery of range information) as a means to achieve predictable response by the robotic system operating in unstructured environments. The fundamental idea is to use nonlinear Lyapunov-based techniques along with photogrammetry methods to overcome the complex control issues and alleviate many of the restrictive assumptions that impact current robotic applications. The outcome of this control methodology is a plug-and-play visual servoing control module that can be utilized in conjunction with current technology such as feature recognition and extraction to enable robotic systems with the capabilities of increased accuracy, autonomy, and robustness, with a larger field of view (and hence a larger workspace). The developed methodology has been reported in numerous peer-reviewed publications and the performance and enabling capabilities of the resulting visual servo control modules have been demonstrated on mobile robot and robot manipulator platforms.
Image Based Visual Servoing For Robotic Systems
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Author :
language : en
Publisher:
Release Date : 2002
Image Based Visual Servoing For Robotic Systems written by and has been published by this book supported file pdf, txt, epub, kindle and other format this book has been release on 2002 with categories.
The objective of this project is to enable current and future EM robots with an increased ability to perceive and interact with unstructured and unknown environments through the use of camera-based visual servo controlled robots. The scientific goals of this research are to develop a new visual servo control methodology that: (1) adapts for the unknown camera calibration parameters (e.g., focal length, scaling factors, camera position and orientation) and the physical parameters of the robotic system (e.g., mass, inertia, friction), (2) compensates for unknown depth information (extract 3D information from the 2D image), and (3) enables multi-uncalibrated cameras to be used as a means to provide a larger field-of-view. Nonlinear Lyapunov-based techniques are being used to overcome the complex control issues and alleviate many of the restrictive assumptions that impact current visual servo controlled robotic systems. The potential relevance of this control methodology will be a plug-and-play visual servoing control module that can be utilized in conjunction with current technology such as feature extraction and recognition, to enable current EM robotic systems with the capabilities of increased accuracy, autonomy, and robustness, with a larger field of view (and hence a larger workspace). These capabilities will enable EM robots to significantly accelerate D & D operations by providing for improved robot autonomy and increased worker productivity, while also reducing the associated costs, removing the human operator from the hazardous environments, and reducing the burden and skill of the human operators.
Visual Servoing In Robotics
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Author : Jorge Pomares
language : en
Publisher: MDPI
Release Date : 2021-08-31
Visual Servoing In Robotics written by Jorge Pomares and has been published by MDPI this book supported file pdf, txt, epub, kindle and other format this book has been release on 2021-08-31 with Technology & Engineering categories.
Visual servoing is a well-known approach to guide robots using visual information. Image processing, robotics, and control theory are combined in order to control the motion of a robot depending on the visual information extracted from the images captured by one or several cameras. With respect to vision issues, a number of issues are currently being addressed by ongoing research, such as the use of different types of image features (or different types of cameras such as RGBD cameras), image processing at high velocity, and convergence properties. As shown in this book, the use of new control schemes allows the system to behave more robustly, efficiently, or compliantly, with fewer delays. Related issues such as optimal and robust approaches, direct control, path tracking, or sensor fusion are also addressed. Additionally, we can currently find visual servoing systems being applied in a number of different domains. This book considers various aspects of visual servoing systems, such as the design of new strategies for their application to parallel robots, mobile manipulators, teleoperation, and the application of this type of control system in new areas.
Enhanced Image Based Visual Servoing Dealing With Uncertainties
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Author : Ahmad Ghasemi
language : en
Publisher:
Release Date : 2020
Enhanced Image Based Visual Servoing Dealing With Uncertainties written by Ahmad Ghasemi and has been published by this book supported file pdf, txt, epub, kindle and other format this book has been release on 2020 with categories.
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.
Visual Servoing
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Author : Koichi Hashimoto
language : en
Publisher: World Scientific
Release Date : 1993
Visual Servoing written by Koichi Hashimoto and has been published by World Scientific this book supported file pdf, txt, epub, kindle and other format this book has been release on 1993 with Technology & Engineering categories.
This book treats visual feedback control of mechanical systems, mostly robot manipulators. It not only deals with image processing techniques and robot control schemes but also covers the latest investigation of the design of the visual servo mechanism based on modern linear and nonlinear control theory, the adaptive control scheme, fuzzy logic, and neural networks. New concepts for utilizing visual sensory information for real-time manipulator control are derived and the performances are evaluated through simulations and/or experiments.The contributors to this book are robotics specialists from all over the world. The book gives a practical perspective on visual servoing to researchers, engineers, and students working in this area.
Image Based Visual Servoing Using Improved Image Moments In 6 Dof Robot Systems
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Author : Sining Liu
language : en
Publisher:
Release Date : 2008
Image Based Visual Servoing Using Improved Image Moments In 6 Dof Robot Systems written by Sining Liu and has been published by this book supported file pdf, txt, epub, kindle and other format this book has been release on 2008 with categories.
Real Time Stereo Visual Servoing Of A 6 Dof Robot For Tracking And Grasping Moving Objects
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Author : Abolfazl Mohebbi
language : en
Publisher:
Release Date : 2013
Real Time Stereo Visual Servoing Of A 6 Dof Robot For Tracking And Grasping Moving Objects written by Abolfazl Mohebbi and has been published by this book supported file pdf, txt, epub, kindle and other format this book has been release on 2013 with categories.
Image Based Visual Servoing Using Trajectory Planning And Augmented Visual Servoing Controller
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Author : Mohammad Keshmiri
language : en
Publisher:
Release Date : 2015
Image Based Visual Servoing Using Trajectory Planning And Augmented Visual Servoing Controller written by Mohammad Keshmiri and has been published by this book supported file pdf, txt, epub, kindle and other format this book has been release on 2015 with categories.
Robots and automation manufacturing machineries have become an inseparable part of industry, nowadays. However, robotic systems are generally limited to operate in highly structured environments. Although, sensors such as laser tracker, indoor GPS, 3D metrology and tracking systems are used for positioning and tracking in manufacturing and assembly tasks, these devices are highly limited to the working environment and the speed of operation and they are generally very expensive. Thus, integration of vision sensors with robotic systems and generally visual servoing system allows the robots to work in unstructured spaces, by producing non-contact measurements of the working area. However, projecting a 3D space into a 2D space, which happens in the camera, causes the loss of one dimension data. This initiates the challenges in vision based control. Moreover, the nonlinearities and complex structure of a manipulator robot make the problem more challenging. This project aims to develop new reliable visual servoing methods that allow its use in real robotic tasks. The main contributions of this project are in two parts; the visual servoing controller and trajectory planning algorithm. In the first part of the project, a new image based visual servoing controller called Augmented Image Based Visual Servoing (AIBVS) is presented. A proportional derivative (PD) controller is developed to generate acceleration as the controlling command of the robot. The stability analysis of the controller is conducted using Lyapanov theory. The developed controller has been tested on a 6 DOF Denso robot. The experimental results on point features and image moment features demonstrate the performance of the proposed AIBVS. Experimental results show that a damped response could be achieved using a PD controller with acceleration output. Moreover, smoother feature and robot trajectories are observed compared to those in conventional IBVS controllers. Later on, this controller is used on a moving object catching process. Visual servoing controllers have shown difficulty in stabilizing the system in global space. Hence, in the second part of the project, a trajectory planning algorithm is developed to achieve the global stability of the system. The trajectory planning is carried out by parameterizing the camera's velocity screw. The camera's velocity screw is parameterized using time-based profiles. The parameters of the velocity profile are then determined such that the velocity profile guides the robot to its desired position. This is done by minimizing the error between the initial and desired features. This method provides a reliable path for the robot considering all robotic constraints. The developed algorithm is tested on a Denso robot. The results show that the trajectory planning algorithm is able to perform visual servoing tasks which are unstable when performed using visual servoing controllers.
Visual Servoing For Robotic Positioning And Tracking Systems
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Author : Yimin Zhao
language : en
Publisher:
Release Date : 2012
Visual Servoing For Robotic Positioning And Tracking Systems written by Yimin Zhao and has been published by this book supported file pdf, txt, epub, kindle and other format this book has been release on 2012 with categories.
Image Based Visual Servoing With Hybrid Camera Configuration For Robust Robotic Grasping
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Author :
language : en
Publisher:
Release Date : 2003
Image Based Visual Servoing With Hybrid Camera Configuration For Robust Robotic Grasping written by and has been published by this book supported file pdf, txt, epub, kindle and other format this book has been release on 2003 with categories.
A challenging anthropomorphic characteristic which a robotic manipulator should acquire is vision. When first introduced to manufacturing and material-handling industries, robots were taught to move "blindly" in a structured environment where the position and the orientation of the manipulated object were assumed to be known. Since then, a spectrum of visual servoing techniques has been developed to increase the versatility and accuracy of the robotic manipulators for carrying out tasks in less structured environments. In particular, the concept of continuous motion control of robotic systems using a visual feedback loop has been applied recently to unstructured environments. In the work presented in this thesis, a functioning mobile manipulator platform, named Autonomous Intelligent Mobile Manipulator (AIMM) with a hybrid camera configuration has been developed. This platform is a member of the cooperative heterogeneous mobile robotic team at the Industrial Automation Laboratory (IAL) of the University of British Columbia (UBC). Given the increasing threat of terrorism and natural disasters around the world, the encompassing research explores new robotic solutions for search and rescue applications. Specifically, the LkL robotics subgroup develops robotic capabilities that can assist or even replace human rescuers in situations that involve life threatening risks. The main contribution of the work in this thesis can be summarized by its two aspects: hardware and control scheme. The developed mobile manipulator consists of a light-weight yet capable manipulator, a mobile robotic base, and a hybrid camera configuration using both a monocular camera and a stereo camera. The classical image-based visual servoing scheme has been improved by techniques of depth estimation and neural network-based grasping. In the present work, both the platform and the control scheme have been tested in real-life scenarios where multiple robots complete a complex task of object handling.