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Providing guidance for maintenance operations using automatic markerless augmented reality system

机译:使用自动无标记增强现实系统为维护操作提供指导

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ABSTRACT Here a real-time Augmented Reality system that assists in maintenance is presented (Figure 1). The novelty of the proposed system relies on its ability of being a complete framework that is self supplied. All the data is extracted automatically during an offlne phase from a collection of 3D parts that are provided as untextured 3D triangle meshes. Our disassembly planning module computes the assembly/disassembly sequence finding collision-free trajectories [1]. Moreover, some basic geometric features, such as edges and junctions, are extracted to address the tracking problem. Additionally, these geometric features let us perform the 3D model recognition, which solves the first camera pose problem and performs the recovery in case of tracking failure [3]. During the online phase, these geometric features are used to build a markerless tracking that updates continuously the camera pose from a monocular image. This markerless tracking combines an edge tracker, a point based tracker and a 3D particle filter to offer a robust 3D tracking against undesirable conditions [2]. Once the camera pose has been computed, the system offers an augmented instruction, indicating how to assemble/disassemble the next part. Thus, the proposed AR system is a complete framework that runs in real-time and tries to facilitate the work of workers, replacing the paper-based documentation.
机译:摘要这里介绍了一个有助于维护的实时增强现实系统(图1)。所提出的系统的新颖性取决于其作为一个完整的,可自行提供的框架的能力。在正式阶段从作为无纹理3D三角形网格提供的3D零件的集合中自动提取所有数据。我们的拆卸计划模块计算装配/拆卸顺序,以找到无碰撞的轨迹[1]。此外,提取了一些基本的几何特征,例如边缘和结,以解决跟踪问题。此外,这些几何特征使我们能够执行3D模型识别,从而解决了第一个相机姿势问题,并在跟踪失败的情况下进行了恢复[3]。在在线阶段,这些几何特征用于建立无标记的跟踪,该跟踪从单眼图像连续更新相机的姿态。这种无标记的跟踪结合了边缘跟踪器,基于点的跟踪器和3D粒子过滤器,可针对不良条件提供可靠的3D跟踪[2]。计算完相机姿势后,系统会提供增强指令,指示如何组装/拆卸下一个零件。因此,拟议的AR系统是一个实时运行的完整框架,它试图代替纸质文档来简化工人的工作。

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