A new algorithm was developed to improve the accuracy of solving problems when both the data and observations are affected by errors and outliers. By incorporating robust estimation techniques, the algorithm can better handle outliers and provide more reliable results. The algorithm was tested in experiments involving line-fitting and 2D affine transformation, demonstrating its effectiveness and robustness.