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Combining visual natural markers and IMU for improved AR based indoor navigation

机译:结合视觉自然标记和IMU以改进基于AR的室内导航

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The operation and maintenance phase is the longest and most expensive life-cycle period of buildings and facilities. Operators need to carry out activities to maintain equipment to prevent functionality failures. Although some software tools have already been introduced, research studies have concluded that (1) facility handover data is still predominantly dispersed, unformatted and paper-based and (2) hence operators still spend 50% of their on-site work on target localization and navigation. To improve these procedures, the authors previously presented a natural marker-based Augmented Reality (AR) framework that digitally supports facility maintenance operators when navigating indoors. Although previous results showed the practical potential, this framework fails if no visual marker is available, if identical markers are at multiple locations, and if markers are light emitting signs. To overcome these shortcomings, this paper presents an improved method that combines an Inertial Measurement Unit (IMU) based step counter and visual live video feed for AR based indoor navigation support. In addition, the AR based marker detection procedure is improved by learning camera exposure times in case of light emitting markers. A case study and experimental results in a controlled environment reveal the improvements and advantages of the enhanced framework.
机译:操作和维护阶段是建筑物和设施的最长和最昂贵的生命周期。操作员需要开展活动来维护设备,以防止功能故障。尽管已经引入了一些软件工具,但是研究研究得出的结论是:(1)设备移交数据仍然主要分散,未格式化且基于纸张,并且(2)因此,运营商仍然将其现场工作的50%用于目标本地化和导航。为了改进这些程序,作者先前提出了一种基于自然标记的增强现实(AR)框架,该框架在室内导航时以数字方式支持设施维护操作员。尽管先前的结果显示了实际的潜力,但是如果没有可用的视觉标记,如果在多个位置使用相同的标记以及标记是发光的标记,则此框架将失败。为了克服这些缺点,本文提出了一种改进的方法,该方法结合了基于惯性测量单元(IMU)的步数计数器和视觉实时视频源,以支持基于AR的室内导航。另外,通过学习在发光标记的情况下的照相机曝光时间,改进了基于AR的标记检测过程。在受控环境中的案例研究和实验结果揭示了增强框架的改进和优势。

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