Towards Multicriterial Scan Planning in Complex 3D Environments

As-is geometry of existing structures in the built environment can be captured with high accuracy using laser scanning. Frequent measurements and automation of data processing steps allow digital representations of physical assets to be kept up to date at a justifiable cost, even if they are subject to frequent changes. Before operators can execute stationary laser scanning, scan planning has to be performed to estimate the required effort and choose equipment, settings, and locations. In contrast to the conventional, expert-based method usually conducted as an assessment in the field, automated offline approaches aim to solve this task exclusively with pre-existing data describing the scene. These methods are more efficient, add transparency to the existing process landscape, and are a prerequisite for sensible implementation of robotic automation, enabling actual repeatability. The novel method proposed in this paper works in complex 3D environments while considering multiple criteria relevant to the feasibility of acquisition and the quality of acquired datasets. The proposed method introduces the scene as a triangulated mesh within which viewpoint candidates are automatically generated. This mesh is further used in a deterministic approach for visibility and coverage analysis between scene and viewpoint candidates. Based on this analysis, viewpoints are selected to form a solution set that fulfils all pre-defined requirements regarding surface coverage in the scene using a greedy algorithm. Connectivity in the solution is enforced to ensure the captured data will allow targetless registration. The objective function used for evaluating potential solutions allows for consideration of all necessary objectives and constraints in the greedy algorithm while retaining flexibility for applying other solution heuristics and optimization methods.