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

Peuzin-Jubert, Manon; Polette, Arnaud; Nozais, Dominique; Mari, Jean-Luc; Pernot, Jean-Philippe

doi:10.1016/j.cad.2021.103094

Cited by 22 publications

(12 citation statements)

References 35 publications

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“…A fundamental part of the IRM paradigm involves the development of smart algorithms and machine learning solutions. Peuzin-Jubert et al [84] recently reviewed state-of-theart methods for optimisation of the measurement view planning of mechanical parts on machine tools, controlled in real time without human intervention, thereby allowing for automated adjustment of machine parameters and tool paths during the fabrication process. Their classification considered a priori knowledge methods (i.e.…”

Section: Information-rich and Data-driven Metrology Approachesmentioning

confidence: 99%

Smart optical coordinate and surface metrology

Catalucci

Thompson

Eastwood

et al. 2022

Meas. Sci. Technol.

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Manufacturing has recently experienced increased adoption of optimised and fast solutions for checking product quality during fabrication, allowing for manufacturing times and costs to be significantly reduced. Due to the integration of machine learning algorithms, advanced sensors and faster processing systems, smart instruments can autonomously plan measurement pipelines, perform decisional tasks and trigger correctional actions as required. In this paper, we summarise the state of the art in smart optical metrology, covering the latest advances in integrated intelligent solutions in optical coordinate and surface metrology, respectively for the measurement of part geometry and surface texture. Within this field, we include the use of a priori knowledge and implementation of machine learning algorithms for measurement planning optimisation. We also cover the development of multi-sensor and multi-view instrument configurations to speed up the measurement process, as well as the design of novel feedback tools for measurement quality evaluation.

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Section: Information-rich and Data-driven Metrology Approachesmentioning

confidence: 99%

Smart optical coordinate and surface metrology

Catalucci

Thompson

Eastwood

et al. 2022

Meas. Sci. Technol.

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“…Point clouds are usually derived from a data acquisition process, also known as reverse engineering. Parts are described by a set of 3D points sampled on the solid surface [171]. 6.…”

Section: Review Work Approachmentioning

confidence: 99%

A review of geometry representation and processing methods for cartesian and multiaxial robot-based additive manufacturing

Lettori

Raffaeli

Bilancia

et al. 2022

Int J Adv Manuf Technol

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Nowadays, robot-based additive manufacturing (RBAM) is emerging as a potential solution to increase manufacturing flexibility. Such technology allows to change the orientation of the material deposition unit during printing, making it possible to fabricate complex parts with optimized material distribution. In this context, the representation of parts geometries and their subsequent processing become aspects of primary importance. In particular, part orientation, multiaxial deposition, slicing, and infill strategies must be properly evaluated so as to obtain satisfactory outputs and avoid printing failures. Some advanced features can be found in commercial slicing software (e.g., adaptive slicing, advanced path strategies, and nonplanar slicing), although the procedure may result excessively constrained due to the limited number of available options. Several approaches and algorithms have been proposed for each phase and their combination must be determined accurately to achieve the best results. This paper reviews the state-of-the-art works addressing the primary methods for the representation of geometries and the subsequent geometry processing for RBAM. For each category, tools and software found in the literature and commercially available are discussed. Comparison tables are then reported to assist in the selection of the most appropriate approaches. The presented review can be helpful for designers, researchers and practitioners to identify possible future directions and open issues.

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“…The increasing performance of 2D and 3D image processing algorithms and the falling prices of electronic components (processors and optical sensors) over the last two decades have motivated not only researchers but also the industry to investigate and automate different machine vision tasks using robot vision systems (RVSs) consisting of a manipulator and a 2D or 3D sensor [1,2]. Whether programmed offline or online, RVSs demand multiple planning modules to execute motion and vision tasks efficiently and robustly.…”

Section: Introductionmentioning

confidence: 99%

“…Whether programmed offline or online, RVSs demand multiple planning modules to execute motion and vision tasks efficiently and robustly. For instance, the efficient and effective planning of valid viewpoints to fulfill a vision task considering different constraints, known as the view(point) planning problem (VPP), still represents an open planning problem within diverse applications [2,3], e.g., camera surveillance, scene exploration, object detection, visual servoing, object reconstruction, image-based inspection, robot calibration, and mobile navigation [2,4].…”

Section: Introductionmentioning

confidence: 99%

Viewpoint Generation Using Feature-Based Constrained Spaces for Robot Vision Systems

et al. 2023

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The efficient computation of viewpoints while considering various system and process constraints is a common challenge that any robot vision system is confronted with when trying to execute a vision task. Although fundamental research has provided solid and sound solutions for tackling this problem, a holistic framework that poses its formal description, considers the heterogeneity of robot vision systems, and offers an integrated solution remains unaddressed. Hence, this publication outlines the generation of viewpoints as a geometrical problem and introduces a generalized theoretical framework based on Feature-Based Constrained Spaces (C-spaces) as the backbone for solving it. A C-space can be understood as the topological space that a viewpoint constraint spans, where the sensor can be positioned for acquiring a feature while fulfilling the constraint. The present study demonstrates that many viewpoint constraints can be efficiently formulated as C-spaces, providing geometric, deterministic, and closed solutions. The introduced C-spaces are characterized based on generic domain and viewpoint constraints models to ease the transferability of the present framework to different applications and robot vision systems. The effectiveness and efficiency of the concepts introduced are verified on a simulation-based scenario and validated on a real robot vision system comprising two different sensors.

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

Cited by 22 publications

References 35 publications

Smart optical coordinate and surface metrology

Smart optical coordinate and surface metrology

A review of geometry representation and processing methods for cartesian and multiaxial robot-based additive manufacturing

Viewpoint Generation Using Feature-Based Constrained Spaces for Robot Vision Systems

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