Eye-to-hand calibration of an industrial robotic arm with structured light 3D cameras

[EN] Computer vision is gaining more and more importance in the world of industrial robotics, since it is necessary to carry out increasingly precise and autonomous tasks, which is why a more exact positioning of the robot is needed. This requires the support of a vision system that is the one that gives the robot precision in its pose, calibrating said system with respect to the robot. This work presents a simple methodology to approach this form of calibration, called hand-eye, using a structured light 3D camera that obtains information from the real world and a six-axis industrial robotic arm. The method uses the RANSAC algorithm for the determination of the planes, which represents a notable reduction in errors, since the coordinates of the points sought come from planes adjusted to thousands of points. This allows the system to always have the ability to obtain a transformation matrix from the coordinates of the camera to the base of the robot. In addition, the proposed method is ideal for making a precision comparison between cameras, due to its simplicity and speed of use. In this study, the resulting error analysis was performed using two dfferent 3D cameras: a basic one (Kinect 360) and an industrial one (Zivid ONE + M).[ES] La visión artificial está cobrando cada día más auge en el mundo de la robótica industrial, ya que es necesario realizar tareas cada vez más precisas y autónomas, por lo que se necesita un posicionamiento del robot más exacto. Para ello se precisa del apoyo de un sistema de visión que sea el que preste al robot precisión en su pose, calibrando dicho sistema con respecto al robot. Este trabajo presenta una metodología sencilla para abordar esta forma de calibración, llamada ojo a mano, empleando una cámara 3D de luz estructurada que obtiene la información del mundo real y un brazo robótico industrial de seis ejes. Esto permite utilizar el algoritmo RANSAC para la determinación de los planos, cuya intersección nos da las coordenadas de los puntos,lo que supone una reducción notable de los errores, ya que las coordenadas proceden de planos ajustados a miles de puntos, lo cual hace que el sistema sea más robusto y capaz de obtener una matriz de transformación de las coordenadas de la cámara a la base del robot, que le permitirá abordar cualquier tarea que precise con una precisión eficiente. Se ha realizado el análisis de errores resultante utilizando dos cámaras 3D diferentes: una básica (Kinect 360) y otra industrial (Zivid ONE+ M).Este trabajo ha sido realizado parcialmente gracias al apoyo del Plan Estatal de Investigación Científica y Técnica y de Innovación 2017-2020 (AUROVI) EQC2018-005190-P. Fernando M. Quintana agradece al Ministerio de Ciencia, Innovación y Universidades de España su apoyo a través de la ayuda FPU (FPU18/04321).Diaz-Cano, I.; Quintana, FM.; Galindo, PL.; Morgado-Estevez, A. (2022). Calibración ojo a mano de un brazo robótico industrial con cámaras 3D de luz estructurada. Revista Iberoamericana de Automática e Informática industrial. 19(2):154-163. https://doi.org/10.4995/riai.2021.16054OJS15416319

Postprocesamiento CAM-ROBOTICA orientado al prototipado y mecanizado en células robotizadas complejas

The main interest of this thesis consists of the study and implementation of postprocessors to adapt the toolpath generated by a Computer Aided Manufacturing (CAM) system to a complex robotic workcell of eight joints, devoted to the rapid prototyping of 3D CAD-defined products. It consists of a 6R industrial manipulator mounted on a linear track and synchronized with a rotary table. To accomplish this main objective, previous work is required. Each task carried out entails a methodology, objective and partial results that complement each other, namely: - It is described the architecture of the workcell in depth, at both displacement and joint-rate levels, for both direct and inverse resolutions. The conditioning of the Jacobian matrix is described as kinetostatic performance index to evaluate the vicinity to singular postures. These ones are analysed from a geometric point of view. - Prior to any machining, the additional external joints require a calibration done in situ, usually in an industrial environment. A novel Non-contact Planar Constraint Calibration method is developed to estimate the external joints configuration parameters by means of a laser displacement sensor. - A first control is originally done by means of a fuzzy inference engine at the displacement level, which is integrated within the postprocessor of the CAM software. - Several Redundancy Resolution Schemes (RRS) at the joint-rate level are compared for the configuration of the postprocessor, dealing not only with the additional joints (intrinsic redundancy) but also with the redundancy due to the symmetry on the milling tool (functional redundancy). - The use of these schemes is optimized by adjusting two performance criterion vectors related to both singularity avoidance and maintenance of a preferred reference posture, as secondary tasks to be done during the path tracking. Two innovative fuzzy inference engines actively adjust the weight of each joint in these tasks.Andrés De La Esperanza, FJ. (2011). Postprocesamiento CAM-ROBOTICA orientado al prototipado y mecanizado en células robotizadas complejas [Tesis doctoral no publicada]. Universitat Politècnica de València. https://doi.org/10.4995/Thesis/10251/10627Palanci

Industrial Robotics

This book covers a wide range of topics relating to advanced industrial robotics, sensors and automation technologies. Although being highly technical and complex in nature, the papers presented in this book represent some of the latest cutting edge technologies and advancements in industrial robotics technology. This book covers topics such as networking, properties of manipulators, forward and inverse robot arm kinematics, motion path-planning, machine vision and many other practical topics too numerous to list here. The authors and editor of this book wish to inspire people, especially young ones, to get involved with robotic and mechatronic engineering technology and to develop new and exciting practical applications, perhaps using the ideas and concepts presented herein

Proceedings of the NASA Conference on Space Telerobotics, volume 1

The theme of the Conference was man-machine collaboration in space. Topics addressed include: redundant manipulators; man-machine systems; telerobot architecture; remote sensing and planning; navigation; neural networks; fundamental AI research; and reasoning under uncertainty

Systems and control : 21th Benelux meeting, 2002, March 19-21, Veldhoven, The Netherlands

Book of abstract

Recent Advances in Indoor Localization Systems and Technologies

Despite the enormous technical progress seen in the past few years, the maturity of indoor localization technologies has not yet reached the level of GNSS solutions. The 23 selected papers in this book present the recent advances and new developments in indoor localization systems and technologies, propose novel or improved methods with increased performance, provide insight into various aspects of quality control, and also introduce some unorthodox positioning methods

Space station systems: A bibliography with indexes (supplement 9)

This bibliography lists 1,313 reports, articles, and other documents introduced into the NASA scientific and technical information system between January 1, 1989 and June 30, 1989. Its purpose is to provide helpful information to researchers, designers and managers engaged in Space Station technology development and mission design. Coverage includes documents that define major systems and subsystems related to structures and dynamic control, electronics and power supplies, propulsion, and payload integration. In addition, orbital construction methods, servicing and support requirements, procedures and operations, and missions for the current and future Space Station are included

Advances in Artificial Intelligence: Models, Optimization, and Machine Learning

The present book contains all the articles accepted and published in the Special Issue “Advances in Artificial Intelligence: Models, Optimization, and Machine Learning” of the MDPI Mathematics journal, which covers a wide range of topics connected to the theory and applications of artificial intelligence and its subfields. These topics include, among others, deep learning and classic machine learning algorithms, neural modelling, architectures and learning algorithms, biologically inspired optimization algorithms, algorithms for autonomous driving, probabilistic models and Bayesian reasoning, intelligent agents and multiagent systems. We hope that the scientific results presented in this book will serve as valuable sources of documentation and inspiration for anyone willing to pursue research in artificial intelligence, machine learning and their widespread applications