Localization of freeform surface workpiece with particle swarm optimization algorithm

A localization method for freeform surface workpiece with particle swarm optimization (PSO) algorithm is proposed in this paper. This study is the first attempt to use PSO as a matching algorithm in localization based on in situ measuring technology. The performance of the algorithm is studied by a set of simulations and optimal parameters settings are given. To test the performance of PSO and compare it with the classical Iterative Closest Point (ICP) algorithm, a blade model and a free-form surface model are used in this study. Simulation results show that PSO with the proposed parameter settings is appropriate to the localization of different freeform surface workpieces with high accuracy and not dependent on pre-localization condition. This study proves that PSO is a new effective algorithm for the localization of freeform surface workpiece because of its advantage of high global search ability over most existing algorithms.