A Solution to the Next Best View Problem for Automated Surface Acquisition

ÐA solution to the anext best viewo (NBV) problem for automated surface acquisition is presented. The NBV problem is to determine which areas of a scanner's viewing volume need to be scanned to sample all of the visible surfaces of an a priori unknown object and where to position/control the scanner to sample them. It is argued that solutions to the NBV problem are constrained by the other steps in a surface acquisition system and by the range scanner's particular sampling physics. A method for determining the unscanned areas of the viewing volume is presented. In addition, a novel representation, positional space (PS), is presented which facilitates a solution to the NBV problem by representing what must be and what can be scanned in a single data structure. The number of costly computations needed to determine if an area of the viewing volume would be occluded from some scanning position is decoupled from the number of positions considered for the NBV, thus reducing the computational cost of choosing one. An automated surface acquisition systems designed to scan all visible surfaces of an a priori unknown object is demonstrated on real