6 research outputs found

    Dense RGB-D SLAM and object localisation for robotics and industrial applications

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    Dense reconstruction and object localisation are two critical steps in robotic and industrial applications. The former entails a joint estimation of camera egomotion and the structure of the surrounding environment, also known as Simultaneous Localisation and Mapping (SLAM), and the latter aims to locate the object in the reconstructed scenes. This thesis addresses the challenges of dense SLAM with RGB-D cameras and object localisation towards robotic and industrial applications. Camera drift is an essential issue in camera egomotion estimation. Due to the accumulated error in camera pose estimation, the estimated camera trajectory is inaccurate, and the reconstruction of the environment is inconsistent. This thesis analyses camera drift in SLAM under the probabilistic inference framework and proposes an online map fusion strategy with standard deviation estimation based on frame-to-model camera tracking. The camera pose is estimated by aligning the input image with the global map model, and the global map merges the information in the images by weighted fusion with standard deviation modelling. In addition, a pre-screening step is applied before map fusion to preclude the adverse effect of accumulated errors and noises on camera egomotion estimation. Experimental results indicated that the proposed method mitigates camera drift and improves the global consistency of camera trajectories. Another critical challenge for dense RGB-D SLAM in industrial scenarios is to handle mechanical and plastic components that usually have reflective and shiny surfaces. Photometric alignment in frame-to-model camera tracking tends to fail on such objects due to the inconsistency in intensity patterns of the images and the global map model. This thesis addresses this problem and proposes RSO-SLAM, namely a SLAM approach to reflective and shiny object reconstruction. RSO-SLAM adopts frame-to-model camera tracking and combines local photometric alignment and global geometric registration. This study revealed the effectiveness and excellent performance of the proposed RSO-SLAM on both plastic and metallic objects. In addition, a case study involving the cover of a electric vehicle battery with metallic surface demonstrated the superior performance of the RSO-SLAM approach in the reconstruction of a common industrial product. With the reconstructed point cloud model of the object, the problem of object localisation is tackled as point cloud registration in the thesis. Iterative Closest Point (ICP) is arguably the best-known method for point cloud registration, but it is susceptible to sub-optimal convergence due to the multimodal solution space. This thesis proposes the Bees Algorithm (BA) enhanced with the Singular Value Decomposition (SVD) procedure for point cloud registration. SVD accelerates the speed of the local search of the BA, helping the algorithm to rapidly identify the local optima. It also enhances the precision of the obtained solutions. At the same time, the global outlook of the BA ensures adequate exploration of the whole solution space. Experimental results demonstrated the remarkable performance of the SVD-enhanced BA in terms of consistency and precision. Additional tests on noisy datasets demonstrated the robustness of the proposed procedure to imprecision in the models

    Play Among Books

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    How does coding change the way we think about architecture? Miro Roman and his AI Alice_ch3n81 develop a playful scenario in which they propose coding as the new literacy of information. They convey knowledge in the form of a project model that links the fields of architecture and information through two interwoven narrative strands in an “infinite flow” of real books

    Forum Bildverarbeitung 2020

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    Image processing plays a key role for fast and contact-free data acquisition in many technical areas, e.g., in quality control or robotics. These conference proceedings of the “Forum Bildverarbeitung”, which took place on 26.-27.11.202 in Karlsruhe as a common event of the Karlsruhe Institute of Technology and the Fraunhofer Institute of Optronics, System Technologies and Image Exploitation, contain the articles of the contributions

    Instrument to Evidence to Argument: Visual Mediation of Invisible Phenomena in Scientific Discourse

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    This dissertation examines how scientists and scientific editors have approached specific problems related to visualization and visual argumentation in scientific texts. These problems are related to the following research questions: (1) How are new visualization practices established as scientifically credible? (2) How do scientists modify existing instrument output to make new visual arguments? (3) How do scientists use verbal and visual means to transform problematic data into acceptable support for novel claims? (4) What are the practical and ethical boundaries of modifying visual artifacts for scientific arguments? (5) How do scientists refute established (but incorrect) visualizations that have been widely accepted as accurate representations of reality? This project considers these issues rhetorically by examining a number of recent and historical cases. The first three case studies explore how scientists created both compelling and uncompelling visual arguments by mediating the visual output of instruments with rhetorical strategies. These case studies focus on visualizations from physical science: x-ray diffraction photographs, graphics establishing the theory of plate tectonics, and visualizations of atmospheric phenomena. In each case, visualizations articulated invisible phenomena in new ways, transforming unclear or seemingly unremarkable data into convincing knowledge claims. My analysis of these cases explores how scientists integrate visuals into the analogical, causal, transitive, symmetrical, and dissociation arguments that are so essential to the practice of science. The later case studies examine broader concerns regarding ethics, persuasion, and modern scientific visualization. I examine recent issues related to the digital generation and manipulation of scientific images and rhetorical issues related to scientists' increasing dependence on complicated computer algorithms for creating visual arguments

    Play Among Books

    Get PDF
    How does coding change the way we think about architecture? Miro Roman and his AI Alice_ch3n81 develop a playful scenario in which they propose coding as the new literacy of information. They convey knowledge in the form of a project model that links the fields of architecture and information through two interwoven narrative strands in an “infinite flow” of real books
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