639 research outputs found

    A cooperative mobile robot and manipulator system (Co-MRMS) for transport and lay-up of fibre plies in modern composite material manufacture

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    Composite materials are widely used in industry due to their light weight and specific performance. Currently, composite manufacturing mainly relies on manual labour and individual skills, especially in transport and lay-up processes, which are time consuming and prone to errors. As part of a preliminary investigation into the feasibility of deploying autonomous robotics for composite manufacturing, this paper presents a case study that investigates a cooperative mobile robot and manipulator system (Co-MRMS) for material transport and composite lay-up, which mainly comprises a mobile robot, a fixed-base manipulator and a machine vision sub-system. In the proposed system, marker-based and Fourier transform-based machine vision approaches are used to achieve high accuracy capability in localisation and fibre orientation detection respectively. Moreover, a particle-based approach is adopted to model material deformation during manipulation within robotic simulations. As a case study, a vacuum suction-based end-effector model is developed to deal with sagging effects and to quickly evaluate different gripper designs, comprising of an array of multiple suction cups. Comprehensive simulations and physical experiments, conducted with a 6-DOF serial manipulator and a two-wheeled differential drive mobile robot, demonstrate the efficient interaction and high performance of the Co-MRMS for autonomous material transportation, material localisation, fibre orientation detection and grasping of deformable material. Additionally, the experimental results verify that the presented machine vision approach achieves high accuracy in localisation (the root mean square error is 4.04 mm) and fibre orientation detection (the root mean square error is 1.84 18) and enables dealing with uncertainties such as the shape and size of fibre plies

    Computer Vision Measurements for Automated Microrobotic Paper Fiber Studies

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    The mechanical characterization of paper fibers and paper fiber bonds determines the key parameters affecting the mechanical properties of paper. Although bulk measurements from test sheets can give average values, they do not yield any real fiber-level data. The current, state-of-the-art methods for fiberlevel measurements are slow and laborious, requiring delicate manual handling of microscopic samples. There are commercial microrobotic actuators that allow automated or tele-operated manipulation of microscopic objects such as fibers, but it is challenging to acquire the data needed to guide such demanding manipulation. This thesis presents a solution to the illumination problem and computer vision algorithms for obtaining the required data. The solutions are designed for a microrobotic platform that comprises actuators for manipulating the fibers and one or two microscope cameras for visual feedback.The algorithms have been developed both for wet fibers, which can be treated as 2D objects, and for dry fibers and fiber bonds, which are treated as 3D objects. The major innovations in the algorithms are the rules for the micromanipulation of the curly fiber strands and the automated 3D measurements of microscale objects with random geometries. The solutions are validated by imaging and manipulation experiments with wet and dry paper fibers and dry paper fiber bonds. In the imaging experiments, the results are compared with the reference data obtained either from an experienced human or another imaging device. The results show that these solutions provide morphological data about the fibers which is accurate and precise enough to enable automated fiber manipulation. Although this thesis is focused on the manipulation of paper fibers and paper fiber bonds, both the illumination solution and the computer vision algorithms are applicable to other types of fibrous materials

    Automation and Robotics: Latest Achievements, Challenges and Prospects

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    This SI presents the latest achievements, challenges and prospects for drives, actuators, sensors, controls and robot navigation with reverse validation and applications in the field of industrial automation and robotics. Automation, supported by robotics, can effectively speed up and improve production. The industrialization of complex mechatronic components, especially robots, requires a large number of special processes already in the pre-production stage provided by modelling and simulation. This area of research from the very beginning includes drives, process technology, actuators, sensors, control systems and all connections in mechatronic systems. Automation and robotics form broad-spectrum areas of research, which are tightly interconnected. To reduce costs in the pre-production stage and to reduce production preparation time, it is necessary to solve complex tasks in the form of simulation with the use of standard software products and new technologies that allow, for example, machine vision and other imaging tools to examine new physical contexts, dependencies and connections

    Human Inspired Multi-Modal Robot Touch

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    Contemporary Robotics

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    This book book is a collection of 18 chapters written by internationally recognized experts and well-known professionals of the field. Chapters contribute to diverse facets of contemporary robotics and autonomous systems. The volume is organized in four thematic parts according to the main subjects, regarding the recent advances in the contemporary robotics. The first thematic topics of the book are devoted to the theoretical issues. This includes development of algorithms for automatic trajectory generation using redudancy resolution scheme, intelligent algorithms for robotic grasping, modelling approach for reactive mode handling of flexible manufacturing and design of an advanced controller for robot manipulators. The second part of the book deals with different aspects of robot calibration and sensing. This includes a geometric and treshold calibration of a multiple robotic line-vision system, robot-based inline 2D/3D quality monitoring using picture-giving and laser triangulation, and a study on prospective polymer composite materials for flexible tactile sensors. The third part addresses issues of mobile robots and multi-agent systems, including SLAM of mobile robots based on fusion of odometry and visual data, configuration of a localization system by a team of mobile robots, development of generic real-time motion controller for differential mobile robots, control of fuel cells of mobile robots, modelling of omni-directional wheeled-based robots, building of hunter- hybrid tracking environment, as well as design of a cooperative control in distributed population-based multi-agent approach. The fourth part presents recent approaches and results in humanoid and bioinspirative robotics. It deals with design of adaptive control of anthropomorphic biped gait, building of dynamic-based simulation for humanoid robot walking, building controller for perceptual motor control dynamics of humans and biomimetic approach to control mechatronic structure using smart materials

    Soft Robot-Assisted Minimally Invasive Surgery and Interventions: Advances and Outlook

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    Since the emergence of soft robotics around two decades ago, research interest in the field has escalated at a pace. It is fuelled by the industry's appreciation of the wide range of soft materials available that can be used to create highly dexterous robots with adaptability characteristics far beyond that which can be achieved with rigid component devices. The ability, inherent in soft robots, to compliantly adapt to the environment, has significantly sparked interest from the surgical robotics community. This article provides an in-depth overview of recent progress and outlines the remaining challenges in the development of soft robotics for minimally invasive surgery
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