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Robot calibration is the process of enhancing the accuracy of a robot by modifying its control software. This book provides a comprehensive treatment of the theory and implementation of robot calibration using computer vision technology. It is the only book to cover the entire process of vision-based robot calibration, including kinematic modeling, camera calibration, pose measurement, error parameter identification, and compensation. The book starts with an overview of available techniques for robot calibration, with an emphasis on vision-based techniques. It then describes various robot-camera systems. Since cameras are used as major measuring devices, camera calibration techniques are reviewed. Camera-Aided Robot Calibration studies the properties of kinematic modeling techniques that are suitable for robot calibration. It summarizes the well-known Denavit-Hartenberg (D-H) modeling convention and indicates the drawbacks of the D-H model for robot calibration. The book develops the Complete and Parametrically Continuous (CPC) model and the modified CPC model, that overcome the D-H model singularities. The error models based on these robot kinematic modeling conventions are presented. No other book available addresses the important, practical issue of hand/eye calibration. This book summarizes current research developments and demonstrates the pros and cons of various approaches in this area. The book discusses in detail the final stage of robot calibration - accuracy compensation - using the identified kinematic error parameters. It offers accuracy compensation algorithms, including the intuitive task-point redefinition and inverse-Jacobian algorithms and more advanced algorithms based on optimal control theory, which are particularly attractive for highly redundant manipulators. Camera-Aided Robot Calibration defines performance indices that are designed for off-line, optimal selection of measurement configurations. It then describes three approaches: closed-form, gradient-based, and statistical optimization. The included case study presents experimental results that were obtained by calibrating common industrial robots. Different stages of operation are detailed, illustrating the applicability of the suggested techniques for robot calibration. Appendices provide readers with preliminary materials for easier comprehension of the subject matter. Camera-Aided Robot Calibration is a must-have reference for researchers and practicing engineers-the only one with all the information!
Describes the details of the calibration process step-by-step, covering systems modeling, measurement, identification, correction and performance evaluation. Calibration techniques are presented with an explanation of how they interact with each other as they are modified. Shows the reader how to determine if, in fact, a robot problem is a calibration problem and then how to analyze it.
Advances in Robotic Systems, Part 1 shows how the activity in robotic systems has increased significantly over the past decade. Major centers of research and development in robotic systems were established on the international scene, and these became focal points for the brilliant research efforts of many academicians and industrial professionals. The systems aspects of robotics, in general, and of robot control, in particular, are manifested through a number of technical facts. This book comprises 10 chapters, with the first focusing on applications of neural networks to robotics. The following chapters then discuss a unified approach to kinematic modeling, identification and compensation for robot calibration; nonlinear control algorithms in robotic systems; and kinematic and dynamic task space motion planning for robot control. Other chapters cover discrete kinematic modeling techniques in Cartesian space for robotic system; force distribution algorithms for multifingered grippers; frequency analysis for a discrete-time robot system; minimum cost trajectory planning for industrial robots; tactile sensing techniques in robotic systems; and sensor data fusion in robotic systems. This book will be of interest to practitioners in the fields of computer science, systems science, and mathematics.
Robot kinematic calibration is the process of enhancing the positioning accuracy of a given manipulator and must be performed after robot manufacture and assembly or during periodical maintenance. This dissertation presents new computationally efficient and robust kinematic calibration algorithms for industrial robots that make use of partial measurements. These include a calibration method that requires the supply of Cartesian coordinates of the calibration points (3DCAL) and another calibration technique that only requires the radial measurements from the calibration points to some reference (1DCAL). Neither method requires orientation measurements nor the explicit knowledge of the where-about of a reference frame. Contrary to most other similar works, both methods make use of a simplified version of the original Denavit-Hartenberg (DH) kinematic model. The simplified DH(-) model has not only proven to be robust and effective in calibrating industrial manipulators but it is also favored from a computational efficiency viewpoint since it consists of comparatively fewer error parameters. We present a conceptual approach to develop a set of guidelines that need to be considered in order to properly construct the DH(-) model such that it is parameterically continuous and non-redundant. We also propose an automated method to provide a characterization of the parameters that can be insightful in identifying redundant/irrelevant parameters and deducing the DH(-) error model of a manipulator. The method is a hybrid scheme comprised of the Simulated Annealing (SA) algorithm and a local solver/optimizer and it conducts a statistical analysis on the estimates of a given error parameter that is indicative of its relevance. For the type of industrial robots used in this dissertation, we made note that calibrating the home position only is sufficient to attain adequate results for most robotics applications. Hence, we put forward for consideration of a yet simpler calibration model; the DH(-)(-) model. We employ the Trust Region (TR) method to minimize the objective functions (solve for the error parameters of the simplified error models) of both frameworks (3DCAL and 1DCAL). We also compare the performance of the proposed methods to that of a state-of-the-art commercial system (Motocal) using the same materials, data and internationally recognized performance standards. Our experimental results suggest that our methods are more robust and yield better results compared to that of MotoCal.
This text presents the latest technology for assessing the performance of machine tools, coordinate measuring machines and robotics. It also details procedures involving international calibration, certification and standardization, and introduces the gear and transmission metrology section.
Robot calibration is the process of enhancing the accuracy of a robot by modifying its control software. This book provides a comprehensive treatment of the theory and implementation of robot calibration using computer vision technology. It is the only book to cover the entire process of vision-based robot calibration, including kinematic modeling, camera calibration, pose measurement, error parameter identification, and compensation. The book starts with an overview of available techniques for robot calibration, with an emphasis on vision-based techniques. It then describes various robot-camera systems. Since cameras are used as major measuring devices, camera calibration techniques are reviewed. Camera-Aided Robot Calibration studies the properties of kinematic modeling techniques that are suitable for robot calibration. It summarizes the well-known Denavit-Hartenberg (D-H) modeling convention and indicates the drawbacks of the D-H model for robot calibration. The book develops the Complete and Parametrically Continuous (CPC) model and the modified CPC model, that overcome the D-H model singularities. The error models based on these robot kinematic modeling conventions are presented. No other book available addresses the important, practical issue of hand/eye calibration. This book summarizes current research developments and demonstrates the pros and cons of various approaches in this area. The book discusses in detail the final stage of robot calibration - accuracy compensation - using the identified kinematic error parameters. It offers accuracy compensation algorithms, including the intuitive task-point redefinition and inverse-Jacobian algorithms and more advanced algorithms based on optimal control theory, which are particularly attractive for highly redundant manipulators. Camera-Aided Robot Calibration defines performance indices that are designed for off-line, optimal selection of measurement configurations. It then describes three approaches: closed-form, gradient-based, and statistical optimization. The included case study presents experimental results that were obtained by calibrating common industrial robots. Different stages of operation are detailed, illustrating the applicability of the suggested techniques for robot calibration. Appendices provide readers with preliminary materials for easier comprehension of the subject matter. Camera-Aided Robot Calibration is a must-have reference for researchers and practicing engineers-the only one with all the information!
Reporting on the latest international standards, calibration and certification procedures, this volume contains the official proceedings of the Fifth International Conference on Laser Metrology, Machine Tool, CMM and Robot Performance. Areas highlighted include: machine tool condition monitoring and calibration; co-ordination of metrology and its application to manufacturing performance and industrial inspection; new techniques in performance assessment and verification; numerical and computational tools.