融合几何特征的ICP改进算法在数字化测量评价中的应用

针对ICP算法对初值依赖程度高、在配准过程中可能陷入局部最优解的问题，提出了一种融合几何特征的ICP改进算法。利用零件具有丰富几何参数的特点，首先对实测点云进行基于曲率的体素采样，尽可能保留几何特征，再将点云的曲率差值和法向量夹角差值引入算法的目标误差函数中进行迭代计算，当目标误差函数达到设定阈值时迭代结束，得到最终配准结果。利用复杂曲面标准件进行了点云配准实验验证，结果表明：相较ICP算法，融合几何特征的ICP改进算法的收敛速度更快、误差更低；相较快速全局配准加ICP配准算法，融合几何特征的ICP改进算法在保证配准准确性的同时，减弱了对初值的需求，简化了点云配准过程。融合几何特征的ICP改进算法为促进零件的准确数字化测量评价提供了有力支撑，具有技术借鉴价值。

Application of improved ICP algorithm incorporating geometric features in digital measurement and evaluation

To address the problem that the ICP algorithm relies heavily on initial values and may fall into local optimum solutions during the alignment process, an improved ICP algorithm incorporating geometric features is proposed. Using the feature that the part has rich geometric parameters, the curvature-based voxel sampling is first performed on the measured point cloud to preserve the geometric features as much as possible, and then the curvature difference and normal vector angle difference of the point cloud are introduced into the target error function of the algorithm for iterative calculation, and the final alignment results are obtained when the target error function reaches a set threshold. Experimental verification of point cloud alignment is carried out using standard parts with complex surfaces, and the results show that the improved ICP algorithm incorporating geometrical features converges faster and has lower errors than the ICP algorithm, and that the improved ICP algorithm incorporating geometrical features reduces the need for initial values and simplifies the point cloud alignment process while maintaining the accuracy of the alignment compared with the fast global registration plus ICP alignment algorithm. The improved ICP algorithm incorporating geometric features provides a strong support to facilitate accurate digital measurement and evaluation of parts, and has a technical reference value.