A six-degrees-of-freedom planning algorithm for the acquisition of complex surfaces

The models produced by means of the available 3D-scanning technologies are considered accurate enough for most applications. Unfortunately, the acquisition of complex objects is still a demanding process that cannot be performed by non-specialists. Among the open problems, one of the most difficult to grasp is the planning of the acquisition session, i.e. choosing a set of positions of the scanner to view the whole surface of the object. Most of the algorithms proposed in the literature either can handle few degrees-of-freedom (DOFs) or are too burdensome, as they require the optimisation of complex objective functions. Hence, they are in trouble when dealing with complex surfaces. We propose a full 6-DOF pose-planning algorithm that is simple and easy to implement. We do not search for the next best view (NBV) to minimise the number of acquisitions, as most previous algorithms do. Rather, we pursue the less ambitious objective of finding a (possibly small) set of views, that guarantee a complete coverage of the surface with a minimum accuracy on the sampled data. Given an incomplete model, unsampled regions are detected and simple patches are built to cover the missing surface. New views are estimated by clustering the normals to unsampled patches.