Metrology-assisted robotic processing of aerospace applications

Jayaweera, Nirosh; Webb, Philip

doi:10.1080/09511920903529255

Cited by 33 publications

(20 citation statements)

References 17 publications

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“…Therefore, if wide-angle lens cameras and camera-systems are going to be utlized for these applications, the most accurate model needs to be determined. Examples of accuracy-dependent applications are robotic manipulation (Nickels et al, 2010;Tamadazte et al, 2011), manufacturing and production part inspection (Jayaweera and Webb, 2010;Schwenke et al, 2002;Shi et al, 2010), and infrastructure deformation monitoring (Detchev et al, 2014;Kwak et al, 2013;Whiteman et al, 2002). This work aims to determine which calibration model is more effective for use in such precision applications.…”

Section: Literature Reviewmentioning

confidence: 99%

Modelling Wide-Angle Lens Cameras for Metrology and Mapping Applications

Jarron¹,

Shahbazi²,

Lichti³

et al. 2019

ISPRS Ann. Photogramm. Remote Sens. Spatial Inf. Sci.

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<p><strong>Abstract.</strong> Wide-angle lenses typically offer fields of view greater than 70&deg;, which are utilized in a variety of imaging, mapping, and navigation applications. Wide-angle lenses are commonly modelled using the central perspective model, compensating for lens distortions through a series of additional parameters. The more extreme the distortions, the further the reality of the lens matches the collinearity equations that define the central perspective model. Fisheye lenses are modelled differently because their fields of view are so wide (typically 180&deg;) that the collinearity model is not applicable. This work studied the effects of modelling wide-angle lenses using both the conventional central perspective model and the fisheye model to determine which model best fits the observations and models the distortions more precisely and accurately. These results were produced by generating observations in a dedicated indoor calibration facility at the University of Calgary: an 11&thinsp;m&thinsp;&times;&thinsp;11&thinsp;m&thinsp;&times;&thinsp;4&thinsp;m field comprising 291 signalized photogrammetry targets. Multiple free-network, self-calibrating bundle adjustments were performed using different models and different cameras. The results of the self-calibrating bundle adjustments were then utilized in a check adjustment on independent sets of check images to validate their accuracy. Two cameras, a Ladybug5 and a GoPro Hero5, were tested. The GoPro was also calibrated using a checkerboard target pattern, and the results were compared to those of the 3D calibration target-field. The results of the bundle adjustments determined that the fisheye model describes the distortions more precisely in both wide-angle camera systems.</p>

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Section: Literature Reviewmentioning

confidence: 99%

Modelling Wide-Angle Lens Cameras for Metrology and Mapping Applications

Jarron¹,

Shahbazi²,

Lichti³

et al. 2019

ISPRS Ann. Photogramm. Remote Sens. Spatial Inf. Sci.

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“…Vision systems and force-torque sensor were used to correct and learn error patterns occurring during various automated processes such as panel forming by Ilangovan [14] and automated polishing by Kalt [15]. Jayaweera [16,17] described a combined metrological and mathematical method to automate aircraft fuselage skin panel assembly. All the above reviewed methods using 2D vision are limited in degrees of freedom and therefore, they are suitable to specific applications.…”

Section: Review Of the Existing Solutionsmentioning

confidence: 99%

Robotic assembly of threaded fasteners in a non-structured environment

Dharmara

Monfared

Ogun

et al. 2018

Int J Adv Manuf Technol

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Over the past two decades, a major part of the manufacturing and assembly market has been driven by the increasing demand for customised products. This has created the need for smaller batch sizes, shorter production times, lower costs, and the flexibility to produce families of products-or to assemble different parts-with the same sets of equipment. Consequently, manufacturing companies have deployed various automation systems and production strategies to improve their resource efficiency and move towards right-first-time production. Threaded fastening operations are widely used in assembly and are typically time-consuming and costly. In high-volume production, fastening operations are commonly automated using jigs, fixtures, and semi-automated tools. However, in low-volume, high-value manufacturing, fastening operations are carried out manually by skilled workers. The existing approaches are found to be less flexible and robust for performing assembly in a less structured industrial environment. This motivated the development of a flexible solution, which does not require fixtures and is adaptable to variation in part locations and lighting conditions. As a part of this research, a novel 3D threaded hole detection and a fast bolt detection algorithms are proposed and reported in this article, which offer substantial enhancement to the accuracy, repeatability, and the speed of the processes in comparison with the existing methods. Hence, the proposed method is more suitable for industrial applications. The development of an automated bolt fastening demonstrator is also described in this article to test and validate the proposed identification algorithms on complex components located in 3D space.

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“…However, these approaches are generally limited to specific applications and offer only limited flexibility. In [20][21][22][23][24][25], some of the most important approaches are represented. They use optical measuring systems to measure the spatial location and orientation of the component.…”

Section: Requirements and State-of-the-artmentioning

confidence: 99%