Autonomous view planning methods for 3D scanning

Abstract

Recent advancements in three-dimensional (3D) scanning technology have broadened its applicability across fields like reverse engineering and autonomous robot navigation, which require a 3D representation of real-world objects. A key aspect of this digitalization process is autonomous view planning. This paper comprehensively reviews autonomous view planning techniques for 3D scanning of unknown or partially known geometries. The objective is to plan optimal scanning paths or views that supplement areas with insufficient or missing data. While the fields of graphics and robotics have approached automatic 3D scanning from different perspectives, they share a common goal of finding optimal views or paths to enhance an object’s 3D digital model. This review examines the essential properties of the autonomous view planning process and classifies selected studies based on these aspects, with research trends visualized through a Sankey diagram. Finally, current limitations are discussed, and future directions necessary for practical implementation are explored.