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李红卫,王岩.基于层级优化点云配准的飞机整机测量技术研究[J].南京航空航天大学学报,2021,53(3):338-343
基于层级优化点云配准的飞机整机测量技术研究
Hierarchical Multiview Point Cloud Registration for Aircraft Measurement
投稿时间:2020-04-13  修订日期:2021-04-13
DOI:10.16356/j.1005-2615.2021.03.002
中文关键词:  点云配准  激光扫描  飞机检测  多视角
英文关键词:point cloud registration  laser scanning  aircraft inspection  multiview
基金项目:国家重点研究发展计划(2019YFB1707504)资助项目。
作者单位邮编
李红卫 中航西安飞机工业集团股份有限公司西安 710089 710089
王岩 南京航空航天大学机电学院南京 210016 210016
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中文摘要:
      飞机产品的精度要求越来越高,这使飞机零件的精确制造和精密装配变得越来越重要。随着数字化测量技术的发展,三维激光扫描仪被广泛应用在飞机产品的多视角局部几何形状捕捉中。将多种角度的点云对齐到同一坐标系中,最终组成测量目标的完整形状,该过程称为配准。因此,多视角点云配准是飞机产品外形重建和检测的重要步骤。针对此问题,提出了基于层级优化的多视角点云配准的通用框架。系统的输入是由位于不同站位的激光扫描仪扫描所得到的带标靶的点云数据,各点云数据处于不同的测量坐标系下且有不同程度的重叠。用图来表达多视角点云和点云之间的重叠关系,图中每个节点表示单站点云数据,节点之间的边表示两点云之间的重叠关系。为使这些点云数据最终匹配到统一的坐标系下,还提出了一系列方法来提高点云配准的精度和效率。
英文摘要:
      In the aviation industry, the demand for high accuracy of the airplane product is growing, which makes precise production of airplane parts and accurate assembly become more and more important. Three-dimensional laser scanner is widely utilized to capture the local shapes, represented by 3D point clouds, of a aircraft product from different viewpoints, followed by aligning various point clouds into the same coordinate system so as to form the entire geometry of the product, which is referred to as registration. Multiview registration of point clouds is therefore a critical step for reconstruction and inspection of aircraft products. The input of the system is the point cloud data with targets obtained by laser scanners at different stations. The point cloud data are in different measurement coordinates systems and have different degrees of overlap. Furthermore, we formulate multiple scan registration refinement as an optimization problem on an undirected graph, where each node and each edge represent a single scan and a connection between two overlapped scans, respectively. The multiple scan registration problem is solved via hierarchical optimization, and thereby the entire geometry shape of the aircraft is accurately obtained. In order to register these point cloud data to a unified coordinate system, a series of methods are proposed to improve the accuracy and efficiency of point cloud registration.
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