10 research outputs found

    A fast 3-D object recognition algorithm for the vision system of a special-purpose dexterous manipulator

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    A fast 3-D object recognition algorithm that can be used as a quick-look subsystem to the vision system for the Special-Purpose Dexterous Manipulator (SPDM) is described. Global features that can be easily computed from range data are used to characterize the images of a viewer-centered model of an object. This algorithm will speed up the processing by eliminating the low level processing whenever possible. It may identify the object, reject a set of bad data in the early stage, or create a better environment for a more powerful algorithm to carry the work further

    CAD-model-based vision for space applications

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    A pose acquisition system operating in space must be able to perform well in a variety of different applications including automated guidance and inspections tasks with many different, but known objects. Since the space station is being designed with automation in mind, there will be CAD models of all the objects, including the station itself. The construction of vision models and procedures directly from the CAD models is the goal of this project. The system that is being designed and implementing must convert CAD models to vision models, predict visible features from a given view point from the vision models, construct view classes representing views of the objects, and use the view class model thus derived to rapidly determine the pose of the object from single images and/or stereo pairs

    Novel metrics and methodology for the characterisation of 3D imaging systems

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    © 2016 The AuthorsThe modelling, benchmarking and selection process for non-contact 3D imaging systems relies on the ability to characterise their performance. Characterisation methods that require optically compliant artefacts such as matt white spheres or planes, fail to reveal the performance limitations of a 3D sensor as would be encountered when measuring a real world object with problematic surface finish. This paper reports a method of evaluating the performance of 3D imaging systems on surfaces of arbitrary isotropic surface finish, position and orientation. The method involves capturing point clouds from a set of samples in a range of surface orientations and distances from the sensor. Point clouds are processed to create a single performance chart per surface finish, which shows both if a point is likely to be recovered, and the expected point noise as a function of surface orientation and distance from the sensor. In this paper, the method is demonstrated by utilising a low cost pan-tilt table and an active stereo 3D camera. Its performance is characterised by the fraction and quality of recovered data points on aluminium isotropic surfaces ranging in roughness average (Ra) from 0.09 to 0.46 µm at angles of up to 55° relative to the sensor over a distances from 400 to 800 mm to the scanner. Results from a matt white surface similar to those used in previous characterisation methods contrast drastically with results from even the dullest aluminium sample tested, demonstrating the need to characterise sensors by their limitations, not just best case performance

    Designing a framework to give perception capabilities to an industrial robot for waste separation tasks

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    El objetivo principal de esta investigación es realizar una primera aproximación para analizar la tarea de preclasificación de residuos de botellas plásticas en Bogotá, que se realiza en el Centro de recolección de La Alquería, uno de los pocos centros de recolección que forman parte de la Unidad Administrativa Especial De Servicios públicos (UASP) y proponer su automatización en una estación de trabajo de coexistencia humano-robot. El proceso es simulado en el Centro Tecnológico de Automatización Industrial (CTAI) de la Universidad Javeriana. El banco de pruebas consiste en una estación de trabajo de preclasificación emulada en la que se clasifican tres tipos de materiales reciclables termoplásticos de los cuales se obtiene su estimación de posición en 3D utilizando el sensor de profundidad IR (infrarrojo) del kinect. Además, el robot Motoman de doble brazo SDA10F equipado con una pinza Robotiq se utiliza para realizar la tarea de Pick and Place, llevando las botellas al contenedor apropiado. Para distribuir el sistema diseñado, se usan dos computadoras portátiles; uno a cargo de ejecutar el algoritmo de procesamiento de imágenes, y otro a cargo de la simulación del entorno y del control del robot.The main purpose of this research is to make a first approach to analyze the waste preclassification task of plastic bottles in Bogota ,that occurs at the Centro de recoleccion La Alqueria one of the few collection centers that are part of the Unidad Administrativa Especial De Servicios Publicos (UASP) and propose its automation in an emulated human-robot co-existence workstation. The process is simulated at the Centro Tecnologico de Automatizacion Industrial (CTAI) from PUJ. The testbed consists on an emulated pre-classification workstation where three types of thermoplastic recyclable materials, are classified and their 3D pose estimation is obtained using the IR (infrared) depth sensor of the Microsoft kinect. Additionally, the SDA10F dual-arm Motoman robot equipped with a Robotiq gripper is used to perform the picking and place task, carrying the bottles to the appropriate bin. To distribute the designed system two laptops are used; one in charge of running the image processing algorithm, and another one in charge of the environment simulation and of the control of the robot.Ingeniero (a) IndustrialPregrad

    Bin Picking – Reposicionamento de peças usando um manipulador

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    A necessidade de introduzir matéria-prima num sistema produtivo é transversal à indústria. No caso em que os objetos chegam de modo desorganizado, dentro de um recipiente estamos perante o problema "bin-picking". Neste contexto, a introdução manual de objetos encontra-se associada à execução do mesmo tipo de movimentos, de um modo repetitivo, durante um elevado número de horas. Como consequência surgem doenças de trabalho, destacando-se as tendinites. Surge, desta forma, a necessidade de uma aplicação de bin-picking. Este tipo de aplicações apresenta potencial, dependendo do hardware e controlo implementado, para aumentar a produtividade, assim como possibilitar a inspeção da totalidade do material inserido no sistema produtivo. A presente dissertação comporta o desenvolvimento e implementação de um sistema automático de reposicionamento de peças, utilizando hardware sensorial de baixo custo e partindo de um caso de estudo associado a uma empresa metalúrgica da região de Leiria. Os objetos a reposicionar, possuem aspeto metálico e são aproximadamente planos. Aos desafios inerentes ao brilho exibido pelas peças acresce a sobreposição entre as mesmas e o erro associado ao sensor de baixo custo e à espessura das peças ser da ordem de grandeza da capacidade de medição de profundidade. Para a resolução deste problema foi utilizado um método com uma etapa de deteção com vista a captura e uma etapa de determinação de pose das peças. Para a etapa de captura foi desenvolvido um método de deteção que utiliza o conceito de procura de uma sub-região. Para a etapa de determinação de pose foi utilizado o algoritmo Iterative Closest Point. O algoritmo, aplicável em tempo real, foi testado com sucesso numa vasta gama de condições de iluminação não controlada (utilizando iluminação normal de uma sala sem qualquer alteração), com a ausência e a presença de sobreposição

    Image understanding and feature extraction for applications in industry and mapping

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    Bibliography: p. 212-220.The aim of digital photogrammetry is the automated extraction and classification of the three dimensional information of a scene from a number of images. Existing photogrammetric systems are semi-automatic requiring manual editing and control, and have very limited domains of application so that image understanding capabilities are left to the user. Among the most important steps in a fully integrated system are the extraction of features suitable for matching, the establishment of the correspondence between matching points and object classification. The following study attempts to explore the applicability of pattern recognition concepts in conjunction with existing area-based methods, feature-based techniques and other approaches used in computer vision in order to increase the level of automation and as a general alternative and addition to existing methods. As an illustration of the pattern recognition approach examples of industrial applications are given. The underlying method is then extended to the identification of objects in aerial images of urban scenes and to the location of targets in close-range photogrammetric applications. Various moment-based techniques are considered as pattern classifiers including geometric invariant moments, Legendre moments, Zernike moments and pseudo-Zernike moments. Two-dimensional Fourier transforms are also considered as pattern classifiers. The suitability of these techniques is assessed. These are then applied as object locators and as feature extractors or interest operators. Additionally the use of fractal dimension to segment natural scenes for regional classification in order to limit the search space for particular objects is considered. The pattern recognition techniques require considerable preprocessing of images. The various image processing techniques required are explained where needed. Extracted feature points are matched using relaxation based techniques in conjunction with area-based methods to 'obtain subpixel accuracy. A subpixel pattern recognition based method is also proposed and an investigation into improved area-based subpixel matching methods is undertaken. An algorithm for determining relative orientation parameters incorporating the epipolar line constraint is investigated and compared with a standard relative orientation algorithm. In conclusion a basic system that can be automated based on some novel techniques in conjunction with existing methods is described and implemented in a mapping application. This system could be largely automated with suitably powerful computers

    The characterisation and simulation of 3D vision sensors for measurement optimisation

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    The use of 3D Vision is becoming increasingly common in a range of industrial applications including part identification, reverse engineering, quality control and inspection. To facilitate this increased usage, especially in autonomous applications such as free-form assembly and robotic metrology, the capability to deploy a sensor to the optimum pose for a measurement task is essential to reduce cycle times and increase measurement quality. Doing so requires knowledge of the 3D sensor capabilities on a material specific basis, as the optical properties of a surface, object shape, pose and even the measurement itself have severe implications for the data quality. This need is not reflected in the current state of sensor haracterisation standards which commonly utilise optically compliant artefacts and therefore can not inform the user of a 3D sensor the realistic expected performance on non-ideal objects.This thesis presents a method of scoring candidate viewpoints for their ability to perform geometric measurements on an object of arbitrary surface finish. This is achieved by first defining a technology independent, empirical sensor characterisation method which implements a novel variant of the commonly used point density point cloud quality metric, which is normalised to isolate the effect of surface finish on sensor performance, as well as the more conventional assessment of point standard deviation. The characterisation method generates a set of performance maps for a sensor per material which are a function of distance and surface orientation. A sensor simulation incorporates these performance maps to estimate the statistical properties of a point cloud on objects with arbitrary shape and surface finish, providing the sensor has been characterised on the material in question.A framework for scoring measurement specific candidate viewpoints is presented in the context of the geometric inspection of four artefacts with different surface finish but identical geometry. Views are scored on their ability to perform each measurement based on a novel view score metric, which incorporates the expected point density, noise and occlusion of measurement dependent model features. The simulation is able to score the views reliably on all four surface finishes tested, which range from ideal matt white to highly polished aluminium. In 93% of measurements, a set of optimal or nearly optimal views is correctly selected.</div

    Proceedings of the NASA Conference on Space Telerobotics, volume 3

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    The theme of the Conference was man-machine collaboration in space. The Conference provided a forum for researchers and engineers to exchange ideas on the research and development required for application of telerobotics technology to the space systems planned for the 1990s and beyond. The Conference: (1) provided a view of current NASA telerobotic research and development; (2) stimulated technical exchange on man-machine systems, manipulator control, machine sensing, machine intelligence, concurrent computation, and system architectures; and (3) identified important unsolved problems of current interest which can be dealt with by future research

    Second Annual Workshop on Space Operations Automation and Robotics (SOAR 1988)

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    Papers presented at the Second Annual Workshop on Space Operation Automation and Robotics (SOAR '88), hosted by Wright State University at Dayton, Ohio, on July 20, 21, 22, and 23, 1988, are documented herein. During the 4 days, approximately 100 technical papers were presented by experts from NASA, the USAF, universities, and technical companies. Panel discussions on Human Factors, Artificial Intelligence, Robotics, and Space Systems were held but are not documented herein. Technical topics addressed included knowledge-based systems, human factors, and robotics
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