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EVALUATION OF VISION-BASED LOCALIZATION AND MAPPING TECHNIQUES IN A SUBSEA METROLOGY SCENARIO

机译:SUBSEEA气象场景中基于视觉的本地化和映射技术的评估

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Metrology is fundamental in all the applications that require to qualify, verify and validate measured data according to standards or, in other words, to assess their compliance with predefined tolerances. At sea, metrology is commonly associated with the process of measuring underwater structures, mainly pipeline elements widely used in offshore industry. Subsea operations are very expensive; optimizing time and money resources are the core factors driving innovation in the subsea metrology industry. In this study, the authors investigate the use of state-of-art vision-based algorithms, i.e. ORB-SLAM2 and Visual Odometry, as a navigation tool to assist and control a Remotely Operated Vehicle (ROV) while performing subsea metrology operations. In particular, the manuscript will focus on methods for assessing the accuracy of both trajectory and tie points provided by the tested approaches and evaluating whether the preliminary real time reconstruction meets the tolerances defined in typical subsea metrology scenarios.
机译:计量学是所有要求根据标准进行合格,验证和确认测量数据的应用程序的基础,换句话说,就是要评估其是否符合预定义的公差。在海上,计量通常与测量水下结构的过程相关,主要是在近海工业中广泛使用的管道元件。海底作业非常昂贵;优化时间和金钱资源是推动海底计量行业创新的核心因素。在这项研究中,作者研究了基于视觉的最新算法,即ORB-SLAM2和视觉里程表法,作为在执行海底计量操作时辅助和控制遥控车(ROV)的导航工具。特别是,该手稿将侧重于评估已测试方法提供的轨迹和联络点的准确性,以及评估初步实时重建是否满足典型海底计量方案中定义的公差的方法。

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