Optimisation of camera positions for optical coordinate measurement based on visible point analysis

Zhang, Hui; Eastwood, Joe; Isa, Mohammed; Sims-Waterhouse, Danny; Leach, Richard; Piano, Samanta

doi:10.1016/j.precisioneng.2020.09.016

Cited by 16 publications

(12 citation statements)

References 37 publications

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“…However, their implementation into the pipeline is still in its infancy. Good practice guides and machine learning algorithms have been developed to optimise measuring procedure and overcome the constraints relating to the user-dependence of many measurement and characterisation protocols [76,119,120]. Further developments are expected to address the current limitations given by measurements held into harsh environments.…”

Section: Discussionmentioning

confidence: 99%

“…In recent years, machine learning algorithms have been developed to optimise the measuring procedure, not only by improving the acquisition and processing of the data, but also by giving the opportunity to automate non-contact instruments, allowing sensors to be repositioned without the need for recalibration of the extrinsic parameters [119]. An example is shown in Fig.…”

Section: User-dependent Constraintsmentioning

confidence: 99%

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Optical metrology for digital manufacturing: a review

Catalucci

Thompson

Piano

et al. 2022

Int J Adv Manuf Technol

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With the increasing adoption of Industry 4.0, optical metrology has experienced a significant boom in its implementation, as an ever-increasing number of manufacturing processes are overhauled for in-process measurement and control. As such, optical metrology for digital manufacturing is currently a hot topic in manufacturing research. Whilst contact coordinate measurement solutions have been adopted for many years, the current trend is to increasingly exploit the advantages given by optical measurement technologies. Smart automated non-contact inspection devices allow for faster cycle times, reducing the inspection time and having a continuous monitoring of process quality. In this paper, a review for the state of the art in optical metrology is presented, highlighting the advantages and impacts of the integration of optical coordinate and surface texture measurement technologies in digital manufacturing processes. Also, the range of current software and hardware technologies for digital manufacturing metrology is discussed, as well as strategies for zero-defect manufacturing for greater sustainability, including examples and in-depth discussions of additive manufacturing applications. Finally, key current challenges are identified relating to measurement speed and data-processing bottlenecks; geometric complexity, part size and surface texture; user-dependent constraints, harsh environments and uncertainty evaluation.

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Section: Discussionmentioning

confidence: 99%

Section: User-dependent Constraintsmentioning

confidence: 99%

Optical metrology for digital manufacturing: a review

Catalucci

Thompson

Piano

et al. 2022

Int J Adv Manuf Technol

Self Cite

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“…Some studies apply a combination of non-model-based and model-based approaches, where previously know geometries are used to train machine learning models, which can later on be a applied to cases where the object to be scanned is unknown. [13][14][15] To perform calculations concerning the geometry of a real-world object, a digital geometric model must exist, which ideally resembles the object perfectly, retaining all its topological details. However, models are usually represented through discretization in the form of a finite set of elements.…”

Section: Virtual Modelmentioning

confidence: 99%

Section: State Of the Artmentioning

confidence: 99%

Model based view planning for the robot-guided automation of optical 3D digitization based on a variable mesh resolution processing approach

Geiger

Sauerbier

Montavon

et al. 2022

Proceedings of the Institution of Mechanical Engineers, Part B:

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The digital 3D representation of manufactured parts plays a crucial role in the quality assurance of small, individualized lot sizes. Machine vision systems, such as optical 3D scanners, guided by an industrial robotic arm, allow for a contactless full digital reconstruction of surface geometries. In order to digitize the whole geometry, it is necessary to acquire 3D scans from multiple viewpoints with respect to the part, which in combination cover the entire surface. With efficiency in mind, this results in an optimization problem between a high surface area coverage and low measurement effort, referred to as the view planning problem. In the presented work, two popular viewpoint candidate generation methods are implemented: Firstly, a surface-based random sampling method, which generates viewpoints within a solution space, in which visibility of a given model surface can be expected. Secondly, a view sphere viewpoint generation approach, which is independent of the object geometry but avoids clustering by generating evenly spaced viewpoints on a sphere around the centre of the object. Using an adjustable remeshing procedure, a multi-stage approach is implemented by generating multiple meshes with different resolutions. Through this, the benefits of working on a coarse mesh, such as fast viewpoint candidate evaluation and selection, are combined with the level of detail of a fine mesh. It is found that it is possible to considerably reduce the mesh resolution while maintaining a reasonably high surface area coverage on a reference model. Applying the proposed procedure to the view planning for a state-of-the-art 3D fringe light projection scanner with highly sophisticated scanning capabilities, it is demonstrated that the view sphere approach is more suitable for this use-case due to the large measurement volumes of the 3D scanner. The frequently used random sampling approach requires an excessively higher computational effort to achieve similar results in comparison.

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“…While the results for their use case are promising, the flight path cannot capture real 3D scenes, as vertical planes like facades cannot be sufficiently covered by nadir imagery. Other approaches such as (Peng and Isler, 2019), (Zhang et al, 2021) or (Bolourian and Hammad, 2020) do not limit the viewpoint positions to a simple plane above the scene with nadir views, but to other geometric primitives like spheres, 3D polygons, 3D boxes, or adaptive rectangles. Even though this allows for better adaption to the real scene geometry, it does not work well for more complex or concave geometries and does not give special consideration to geometric features like edges.…”

Section: Existing Approachesmentioning

confidence: 99%

Evaluation of 3d Uas Flight Path Planning Algorithms

Debus

Rodehorst

2021

Int. Arch. Photogramm. Remote Sens. Spatial Inf. Sci.

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Abstract. The application of image-based methods in inspections and monitoring has increased significantly over recent years. This is especially the case for the inspection of large structures that are not easily accessible for human inspectors. Here, unmanned aircraft systems (UAS) can support by generating high-quality images, that contain valuable information about the structure’s condition. To guarantee high quality and completeness for the acquired data, inspection missions are planned in advance by computing a flight path for the UAS, that covers the entire structure with the required quality. Many approaches on this topic exist that aim to solve this planning task. Nevertheless, each publication on this matter mostly stands on its own, working with its own criteria and no comparison to other approaches. Therefore, it is currently not possible to compare different approaches and select the most suitable for a specific scenario. To solve this problem, this work proposes an evaluation pipeline that applies well defined quality criteria on flight paths for close-range image-based inspections. These criteria are limited to fundamental aspects for the evaluation of paths that were created for diverse scenarios with diverse criteria and still find common ground for comparison. As experiments show, this pipeline allows the comparison of different approaches, objectifying the performance and working towards a common understanding of the current state of the art. Finally, the Bauhaus Path Planning Challenge is presented, inviting submissions to a comparison based on this pipeline to collaborate on an objective ranking, available under https://uni-weimar.de/pathplanning.

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Optimisation of camera positions for optical coordinate measurement based on visible point analysis

Cited by 16 publications

References 37 publications

Optical metrology for digital manufacturing: a review

Optical metrology for digital manufacturing: a review

Model based view planning for the robot-guided automation of optical 3D digitization based on a variable mesh resolution processing approach

Evaluation of 3d Uas Flight Path Planning Algorithms

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