Viewpoints Planning for Active 3-D Reconstruction of Profiled Blades Using Estimated Occupancy Probabilities (EOP)

Abstract

Reconstructing 3-D models of blades plays an increasingly important role in manufacturing. However, the scanning equipment cannot acquire a complete model of a blade with one scanning due to its discontinuous and complex spatial surface. How to plan the viewpoints in presence of the thin walled and free-form properties of blades is a challenging task. In this article, we propose a novel viewpoint planning algorithm using estimated occupancy probabilities. Existing viewpoint planning methods do not consider the enough overlaps, which are important for data registration. We predict surface overlaps using an estimated OctoMap. OctoMap is an efficient probabilistic framework for 3-D occupancy grid mapping. However, the occupancy probabilities of occluded voxels in the original OctoMap remain unknown, which makes it impossible to calculate the overlap of candidate viewpoints. Hence, a recursive Bayesian filter is designed to estimate occupancy probabilities of occluded voxels. With more specific occupancy probabilities, the overlap of a viewpoint is predicted by the ray tracing technology. Experiments on four different profiled blades synthetic datasets show that our algorithm outperforms existing methods in terms of controlling overlap rate. The efficiency of our method is confirmed by real world experiments with low registration failure frequency in reconstruction.