Estimation of Point Cloud Object Pose Using Particle Swarm Optimization

In this paper, we deal with the problem of pose estimation based on point cloud. We modify the Iterative closest face (ICF) algorithm by mathematical techniques, in which a new method to calculate point-face distance with less computational cost is proposed. Then, we combine this algorithm with particle swarm optimization to get a better searched result. PSO is employed because there are few parameters to adjust and it is more efficient than the original searched method in ICF. A set of experiments is conducted, following the statistical analysis of the results. These experiments demonstrate the accuracy and robustness of our algorithm.