203 research outputs found

    Robonaut Mobile Autonomy: Initial Experiments

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    A mobile version of the NASA/DARPA Robonaut humanoid recently completed initial autonomy trials working directly with humans in cluttered environments. This compact robot combines the upper body of the Robonaut system with a Segway Robotic Mobility Platform yielding a dexterous, maneuverable humanoid ideal for interacting with human co-workers in a range of environments. This system uses stereovision to locate human teammates and tools and a navigation system that uses laser range and vision data to follow humans while avoiding obstacles. Tactile sensors provide information to grasping algorithms for efficient tool exchanges. The autonomous architecture utilizes these pre-programmed skills to form complex behaviors. The initial behavior demonstrates a robust capability to assist a human by acquiring a tool from a remotely located individual and then following the human in a cluttered environment with the tool for future use

    Investigation and development of a flexible gripper with adaptable finger geometry

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    Das zuverlässige und schonende Greifen ist ein Hauptanliegen bei der Entwicklung von neuartigen Greifvorrichtungen. Je größer die Kontaktfläche zwischen dem Greifer und dem Greifobjekt ist, desto schonender und zuverlässiger ist der Greifvorgang. Um dieses Ziel zu erreichen wurden in den letzten Jahrzehnten zahlreiche Untersuchungen zu adaptiven passiven Greifern durchgeführt. Ein neuer Forschungszweig im Bereich selbstadaptiver Greifer sind Greifer mit nachgiebigen blattfederartigen Greifelementen (Greiferfinger) Die Funktionsweise basiert auf dem elastischen Ausknicken der Greifelemente infolge einer translatorische Antriebsbewegung Die vorliegende Arbeit konzentriert sich auf die Verbesserung des Greifvorgangs, indem die Kontaktlänge zwischen den blattfederartigen Greiferfingern und dem zu greifenden Objekt deutlich erhöht wird. Um diese Aufgabenstellung zu lösen, muss eine geeignete Greifergeometrie für ein gegebenes Greifobjekt berechnet werden. Die gezielte Berechnung der erfoderlichen Greifergeometrie für ein bekanntes Greifobjekt ist nicht möglich. Daher wurde als Lösungsansatz die umkehrte Richtung gewählt. Für eine definierte Greifgeometrie wird die Gestalt des dazu passenden “idealen” Greifobjektes ermittelt und anschließend mit der Gestalt zu greifenden Objektes verglichen. Bei Gestaltabweichungen wird die Greifergeometrie iterative verändert, bis seine geeignete Greifergeometrie gefunden wurde. Im Rahmen der vorliegenden Arbeit wird zunächst die Ermittlung des “idealen” Greifobjektes behandelt. Es wurde ein Algorithmus entwickelt, der für eine vorgegebene Greifergeometrie die Gestalt eines runden bzw. elliptischen Objektes ermittelt. Der Algorithmus verwendet als Eingabedaten die Biegelinien der elastisch ausgeknickten Greiffinger unter Berücksichtigung unterschiedlicher Randbedingungen. Als Ausgabedaten liefert der Algorithmus die Gestalt des passenden Greifobjektes zurück. Für quadratische bzw. rechteckige sowie für dreieckige Objekte wurden unterschiedliche Greifgeometrien untersucht. Außerdem wird für quadratische und rechteckige Objekte das Lösungskonzept für die Entwicklung eines weiteren Algorithmus beschrieben. In Kapitel 1 wird eine Klassifizierung von Greifern basierend auf der Anpassungsfähigkeit vorgestellt. In Kapitel 2 werden Lösungskonzepte, Modelle und Theorien vorgestellt. In Kapitel 3 werden Ablaufdiagramme der Algorithmen dargestellt. In Kapitel 4 wird die Entwicklung des Algorithmus für elliptische Objekte und deren Betriebsmodi beschrieben. In Kapitel 5 werden Greifgeometrien für quadratische bzw. Rechteckige sowie für dreieckige Objekte analysiert und die Ideen eines Algorithmus für quadratisch bzw. rechteckige Objekte beschrieben. In Kapitel 6 wird ein kurzer Überblick über die zukünftige Arbeiten.Reliable and gentle gripping is a major concern in the development of new gripping devices. The larger contact surface between the gripper and the gripping object, the gentler and more reliable the gripping process. In order to achieve this goal, further investigations on adaptive passive grippers have been carried out in the recent decades. A new branch of research in the field of self-adaptive grippers are compliant leaf-spring-like gripping elements (gripper fingers). Its mode of operation is based on the elastic buckling of the gripping elements as a result of a translatory drive movement. The present work focuses on improving the gripping process by increasing significantly the contact length between the compliant leaf-spring-like gripper fingers and the object to be gripped. In order to solve this task, a suitable gripper geometry for a given gripping object should be calculated The specific calculation of the required gripper geometry for a known gripping object is not possible; therefore, this work aims in the opposite direction. For a defined gripping geometry, the shape of the matching “ideal” gripping object is determined and then compared with the desired object to be gripped. In case of a deviation in the size, the gripper geometry is iteratively changed until its suitable gripper geometry has been found. In the present work, the determination of the “ideal” gripping object is the first task to deal with. An algorithm has been developed to determine the shape of a round-elliptical object for a given gripper geometry. The algorithm uses as data input the bend lines of the compliant twogripper finger under different boundary conditions. As data output, the algorithm returns the shape of the matching gripping object. For square-rectangular and triangular objects, different gripping geometries have been investigated. Furthermore, for square-rectangular objects, solution concepts for the development of an algorithm is described. In chapter 1, a classification based on adaptability is presented. In chapter 2, solution concepts, models and theories involved are introduced. In chapter 3, process flow diagrams of the algorithms are presented. In chapter 4, the development of the algorithm for elliptical objects and its operation modes are described. In chapter 5, gripping geometries for square-rectangular and triangular objects are analysed and the ideas of an algorithm for square-rectangular objects are described. In chapter 6, a brief overview of the futur work is commented.Tesi

    Automated freeform assembly of threaded fasteners

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    Over the past two decades, a major part of the manufacturing and assembly market has been driven by its customer requirements. Increasing customer demand for personalised products create the demand for smaller batch sizes, shorter production times, lower costs, and the flexibility to produce families of products - or different parts - with the same sets of equipment. Consequently, manufacturing companies have deployed various automation systems and production strategies to improve their resource efficiency and move towards right-first-time production. However, many of these automated systems, which are involved with robot-based, repeatable assembly automation, require component- specific fixtures for accurate positioning and extensive robot programming, to achieve flexibility in their production. Threaded fastening operations are widely used in assembly. In high-volume production, the fastening processes are commonly automated using jigs, fixtures, and semi-automated tools. This form of automation delivers reliable assembly results at the expense of flexibility and requires component variability to be adequately controlled. On the other hand, in low- volume, high- value manufacturing, fastening processes are typically carried out manually by skilled workers. This research is aimed at addressing the aforementioned issues by developing a freeform automated threaded fastener assembly system that uses 3D visual guidance. The proof-of-concept system developed focuses on picking up fasteners from clutter, identifying a hole feature in an imprecisely positioned target component and carry out torque-controlled fastening. This approach has achieved flexibility and adaptability without the use of dedicated fixtures and robot programming. This research also investigates and evaluates different 3D imaging technology to identify the suitable technology required for fastener assembly in a non-structured industrial environment. The proposed solution utilises the commercially available technologies to enhance the precision and speed of identification of components for assembly processes, thereby improving and validating the possibility of reliably implementing this solution for industrial applications. As a part of this research, a number of novel algorithms are developed to robustly identify assembly components located in a random environment by enhancing the existing methods and technologies within the domain of the fastening processes. A bolt identification algorithm was developed to identify bolts located in a random clutter by enhancing the existing surface-based matching algorithm. A novel hole feature identification algorithm was developed to detect threaded holes and identify its size and location in 3D. The developed bolt and feature identification algorithms are robust and has sub-millimetre accuracy required to perform successful fastener assembly in industrial conditions. In addition, the processing time required for these identification algorithms - to identify and localise bolts and hole features - is less than a second, thereby increasing the speed of fastener assembly

    Non-destructive technologies for fruit and vegetable size determination - a review

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    Here, we review different methods for non-destructive horticultural produce size determination, focusing on electronic technologies capable of measuring fruit volume. The usefulness of produce size estimation is justified and a comprehensive classification system of the existing electronic techniques to determine dimensional size is proposed. The different systems identified are compared in terms of their versatility, precision and throughput. There is general agreement in considering that online measurement of axes, perimeter and projected area has now been achieved. Nevertheless, rapid and accurate volume determination of irregular-shaped produce, as needed for density sorting, has only become available in the past few years. An important application of density measurement is soluble solids content (SSC) sorting. If the range of SSC in the batch is narrow and a large number of classes are desired, accurate volume determination becomes important. A good alternative for fruit three-dimensional surface reconstruction, from which volume and surface area can be computed, is the combination of height profiles from a range sensor with a two-dimensional object image boundary from a solid-state camera (brightness image) or from the range sensor itself (intensity image). However, one of the most promising technologies in this field is 3-D multispectral scanning, which combines multispectral data with 3-D surface reconstructio

    3D Shape Perception from Monocular Vision, Touch, and Shape Priors

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    Perceiving accurate 3D object shape is important for robots to interact with the physical world. Current research along this direction has been primarily relying on visual observations. Vision, however useful, has inherent limitations due to occlusions and the 2D-3D ambiguities, especially for perception with a monocular camera. In contrast, touch gets precise local shape information, though its efficiency for reconstructing the entire shape could be low. In this paper, we propose a novel paradigm that efficiently perceives accurate 3D object shape by incorporating visual and tactile observations, as well as prior knowledge of common object shapes learned from large-scale shape repositories. We use vision first, applying neural networks with learned shape priors to predict an object's 3D shape from a single-view color image. We then use tactile sensing to refine the shape; the robot actively touches the object regions where the visual prediction has high uncertainty. Our method efficiently builds the 3D shape of common objects from a color image and a small number of tactile explorations (around 10). Our setup is easy to apply and has potentials to help robots better perform grasping or manipulation tasks on real-world objects.Comment: IROS 2018. The first two authors contributed equally to this wor

    Measurement Strategies for Object Identification

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    Development of an automated robot vision component handling system

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    Thesis (M. Tech. (Engineering: Electrical)) -- Central University of technology, Free State, 2013In the industry, automation is used to optimize production, improve product quality and increase profitability. By properly implementing automation systems, the risk of injury to workers can be minimized. Robots are used in many low-level tasks to perform repetitive, undesirable or dangerous work. Robots can perform a task with higher precision and accuracy to lower errors and waste of material. Machine Vision makes use of cameras, lighting and software to do visual inspections that a human would normally do. Machine Vision is useful in application where repeatability, high speed and accuracy are important. This study concentrates on the development of a dedicated robot vision system to automatically place components exiting from a conveyor system onto Automatic Guided Vehicles (AGV). A personal computer (PC) controls the automated system. Software modules were developed to do image processing for the Machine Vision system as well as software to control a Cartesian robot. These modules were integrated to work in a real-time system. The vision system is used to determine the parts‟ position and orientation. The orientation data are used to rotate a gripper and the position data are used by the Cartesian robot to position the gripper over the part. Hardware for the control of the gripper, pneumatics and safety systems were developed. The automated system‟s hardware was integrated by the use of the different communication protocols, namely DeviceNet (Cartesian robot), RS-232 (gripper) and Firewire (camera)

    Intelligent gripper design and application for automated part recognition and gripping

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    Intelligent gripping may be achieved through gripper design, automated part recognition, intelligent algorithm for control of the gripper, and on-line decision-making based on sensory data. A generic framework which integrates sensory data, part recognition, decision-making and gripper control to achieve intelligent gripping based on ABB industrial robot is constructed. The three-fingered gripper actuated by a linear servo actuator designed and developed in this project for precise speed and position control is capable of handling a large variety of objects. Generic algorithms for intelligent part recognition are developed. Edge vector representation is discussed. Object geometric features are extracted. Fuzzy logic is successfully utilized to enhance the intelligence of the system. The generic fuzzy logic algorithm, which may also find application in other fields, is presented. Model-based gripping planning algorithm which is capable of extracting object grasp features from its geometric features and reasoning out grasp model for objects with different geometry is proposed. Manipulator trajectory planning solves the problem of generating robot programs automatically. Object-oriented programming technique based on Visual C++ MFC is used to constitute the system software so as to ensure the compatibility, expandability and modular programming design. Hierarchical architecture for intelligent gripping is discussed, which partitions the robot’s functionalities into high-level (modeling, recognizing, planning and perception) layers, and low-level (sensing, interfacing and execute) layers. Individual system modules are integrated seamlessly to constitute the intelligent gripping system
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