The manual 3D digitization process is expensive since it requires a highly trained technician who decides about the different views needed to acquire the object model. The quality of the final result strongly depends, in addition to the complexity of the object shape, on the selected viewpoints and thus on the human expertise. Nowadays, the most developed digitization strategies in industry are based on a teaching approach in which a human operator manually determines one set of poses for the ranging device. The main drawback of this methodology is the influence of the operator's expertise. Moreover, this technique does not fulfill the high level requirement of industrial applications which require reliable, repeatable, and fast programming routines.My thesis project focuses on the definition of a procedure for automatic and intelligent 3D digitization. This procedure is presented as a sequence of processes that are essentially the view planning, the motion planning, the acquisition and the post-processing of the acquired data. The advantage of our procedure is that it is generic since it is not performed for a specific scanning system. Moreover, it is not dependent on the methods used to perform the tasks associated with each elementary process. We also developed three view planning methods to generate a complete 3D model of unknown and complex objects that we implemented on a robotic cell. Our methods enable fast and complete 3D reconstruction while moving efficiently the scanner. Additionaly, our approaches are applicable to all kinds of range sensors.
