Registration of 3-D Shape with Free-Form Surface Using Imageware and Genetic Algorithm

Abstract

Registration of 3-D shape is significant in quantizing the error between the part and its CAD model and evaluating the part's manufacturing accuracy. In the past, various improved methods of the iterative closest point (ICP) had been proposed in registration. However, without fine initial pose of point clouds, the ICP algorithm often could not converge to the best (or near best) solution. According to the characteristics of 3-D shape with free-form surface, a new method for registration of 3-D shape with free-form surface is given, by which there are not rigid requests in initial pose of point data and the 3-D shape model could be in arbitrary positions and orientations in space. To improve the efficiency and accuracy of solving, this method is divided into general registration and fine registration. General registration is to fit rapidly and roughly the measured point cloud to designing point cloud from CAD model by Imageware. Fine registration is to further accurately fit the two group points using genetic algorithm (GA). Case study is finally given for a work piece with free-form surface to show the effectiveness of the above method.