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Survey on the View Planning Problem for Reverse Engineering and Automated Control Applications

Article dans une revue avec comité de lecture
Author
PEUZIN-JUBERT, Manon
543315 Laboratoire d’Ingénierie des Systèmes Physiques et Numériques [LISPEN]
1084037 I-MC (Innovative Manufacturing and Controls)
198056 Aix Marseille Université [AMU]
POLETTE, Arnaud
543315 Laboratoire d’Ingénierie des Systèmes Physiques et Numériques [LISPEN]
NOZAIS, Dominique
1084037 I-MC (Innovative Manufacturing and Controls)
MARI, Jean-Luc
198056 Aix Marseille Université [AMU]
PERNOT, Jean-Philippe
543315 Laboratoire d’Ingénierie des Systèmes Physiques et Numériques [LISPEN]

URI
http://hdl.handle.net/10985/22855
DOI
10.1016/j.cad.2021.103094
Date
2021-12
Journal
Computer-Aided Design

Abstract

At present, optical sensors are being widely used to realize high quality control or reverse engineering of products, systems, buildings, environments or human bodies. Although the intrinsic characteristics of such breakthrough technologies may vary, ensuring complete acquisition relies on the definition of the optimal acquisition planning. To this end, the view planning problem (VPP) must be solved to automatically determine the optimal positions and/or trajectories of the acquisition devices to fully cover the part to be digitized. Such an automatization of the entire acquisition process is of considerably interest in the context of Industry 4.0. The aim of this paper is to review the state of the art works addressing the view planning problem and to identify the future challenges and possible research directions. First, the paper introduces a set of criteria to analyze the available methods, grouped into several macrocategories. The categories are presented and formalized to clearly understand the backbone and similarities of the grouped methods. Second, the paper describes and characterizes the available methods, based on their analysis according to the adopted criteria. The results of this extensive analysis clearly highlight the open issues and future challenges.

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