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Development of Registration methodology to 3-D Point Clouds in Robot Scanning

机译:机器人扫描中3D点云的配准方法开发

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The problem of multi-view 3-D point clouds registration is investigated and effectively resolved by the developed methodology. A registration method is proposed to register two series of scans into an object model by using the proposed oriented-bounding-box (OBB) regional area-based descriptor. Robot 3-D scanning is often employed to generate set of point clouds of physical objects. The automated operation has to successively digitize view-dependent area-scanned point clouds from complex shaped objects by multi-view point clouds registration. To achieve this, the OBB regional area-based descriptor is employed to determine an initial transformation matrix and is then refined employing iterative closest point (ICP) algorithm. The developed method can be used to resolve the commonly encountered difficulty in accurately merging two neighbouring area-scanned images when no coordinate reference exists. The developed method has been verified through some experimental tests for its registration accuracy. Experimental results have preliminarily demonstrated the feasibility of the developed method.Key words: Robot / 3-D scanning / image registration / point clouds / reverse engineering / surface digitization
机译:通过开发的方法研究并有效解决了多视图3-D点云配准问题。提出了一种注册方法,该方法使用提议的定向边界框(OBB)基于区域的区域描述符将两个系列的扫描注册到对象模型中。机器人3-D扫描通常用于生成一组物理对象的点云。自动化操作必须通过多视点云配准将来自复杂形状物体的视点相关区域扫描点云连续数字化。为了实现这一点,使用OBB基于区域的描述符来确定初始转换矩阵,然后使用迭代最近点(ICP)算法对其进行精炼。所开发的方法可用于解决在不存在坐标参考的情况下准确合并两个相邻的区域扫描图像时经常遇到的困难。通过一些实验测试验证了该开发方法的对准精度。实验结果初步证明了该方法的可行性。关键词:机器人/ 3D扫描/图像配准/点云/逆向工程/表面数字化

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