论文部分内容阅读
针对三维测量数据和自由曲面模型之间的位姿配准问题,研究了先粗后精的两步配准方法。在初始配准的基础上,融合最小二乘法和最小条件原则构造目标函数,应用微分进化算法对目标函数寻优,找出三维测量数据与理论曲面的最佳匹配矩阵以实现最优配准。实验结果表明,该方法与遗传算法相比具有运算速度快和精度高等特点,能较好的解决复杂曲面类零件测量数据的位姿配准问题,并且可用于逆向工程中曲面误差的分析及修正。
Aiming at the pose registration between 3D measurement data and freeform surface model, a two-step registration method is developed. On the basis of the initial registration, the objective function is constructed based on the principle of least squares and minimum conditions. The differential evolution algorithm is used to optimize the objective function, and the optimal matching matrix between the three-dimensional measured data and the theoretical surface is found to achieve the optimal registration. The experimental results show that the proposed method has the advantages of fast computing speed and high accuracy compared with genetic algorithm, and can well solve the pose registration problem of complex surface type measurement data, and can be used to analyze and correct the surface error in reverse engineering .