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Flexible registration method for light-stripe sensors considering sensor misalignments

机译:考虑传感器未对流的光条传感器的灵活注册方法

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In many application areas such as object reconstruction or quality assurance, it is required to completely or partly measure the shape of an object or at least the cross section of the required object region. For complex geometries, therefore, multiple views are needed to bypass undercuts respectively occlusions. Hence, a multi-sensor measuring system for complex geometries has to consist of multiple light-stripe sensors that are surrounding the measuring object in order to complete the measurements in a prescribed time. The number of sensors depends on the object geometry and dimensions. In order to create a uniform 3D data set from the data of individual sensors, a registration of each individual data set into a common global coordinate system has to be performed. Stateof-the-art registration methods for light-stripe sensors use only data from object intersection with the respective laser plane of each sensor. At the same time the assumption is met that all laser planes are coplanar and that there are corresponding points in two data sets. However, this assumption does not represent the real case, because it is nearly impossible to align multiple laser planes in the same plane. For this reason, sensor misalignments are neglected by this assumption. In this work a new registration method for light-stripe sensors is presented that considers sensor misalignments as well as intended sensor displacements and tiltings. The developed method combines 3D pose estimation and triangulated data to properly register the real sensor pose in 3D space.
机译:在许多应用领域,例如对象重建或质量保证,需要完全或部分地测量物体的形状或至少所需对象区域的横截面。因此,对于复杂的几何形状,需要多种视图旁路底切堵塞。因此,复杂几何形状的多传感器测量系统必须由周围的测量对象周围的多个光条传感器组成,以便在规定时间内完成测量。传感器的数量取决于对象几何形状和尺寸。为了从各个传感器的数据设置统一的3D数据,必须执行将每个单独数据的登记到公共全局坐标系中。灯条传感器的态度 - 艺术注册方法仅使用来自对象交叉点的数据与每个传感器的各个激光器相交。同时满足假设,所有激光平面都是共面的,并且两个数据集中存在对应的点。然而,这种假设不代表实际情况,因为几乎不可能在同一平面中对准多个激光平面。因此,通过这种假设忽略了传感器未对流。在这项工作中,提出了一种新的光条传感器登记方法,其考虑传感器错位以及预期的传感器位移和倾斜。开发方法结合了3D姿势估计和三角化数据以正确地注册3D空间中的真实传感器姿势。

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