Robodome imaging for high performance manufactured aerostructures
Lead Research Organisation:
UNIVERSITY COLLEGE LONDON
Department Name: Civil Environmental and Geomatic Eng
Abstract
The next generation of energy-efficient aircraft require highly optimised aerodynamic wing surfaces engineered to increasingly tight tolerances manufactured at increasing rates of production. To facilitate this, high accuracy spatial information is required both at component interfaces and product critical surfaces to understand the manipulations needed to fit part-to-part, the impact of resultant distortions in the parts and any necessary rework. Downstream opportunities extend over the manufacturing cycle, to support adaptations in product design, materials and processes needed to optimise quality, cost, and productivity.
Challenging this activity are existing large volume metrology systems and deployments failing to achieve diverse engineering requirements; being too costly or needing deployments that disrupt or stop the manufacturing process. For current products metrology activities in aircraft wing manufacture are largely turn-key and consume over 25% of Airbus production time. In a systems paradigm that mirrors satellite navigation data and its now ubiquitous reliance for in-car and mobile phone navigation, improvement in productivity and flexibility to support new processes requires richer trustworthy spatial data from systems that are embedded into manufacturing infrastructure. Whilst capable systems are available at small to medium volumes and with innovation funding will evolve into industrial sensor networks, a research and technology gap in large-volume marker less surface metrology limits opportunity. Addressing the "tools to support the verification of models, metrology in manufacturing" theme of this EPSRC call, our proposal seeks to close the gap.
Our vision is to embed low-cost Reflectance Transformation Imaging guided by virtual optical metrology instrument models into factory spaces to achieve accuracies of the order of a few micrometres over areas of several tens of square metres. Airbus supports the PI through an REng/Airbus Chair in Large-Volume Metrology enabling R&T collaboration and access to specialists including manufacturing architects who design the digital factories of the future. Together we have co-created this proposal and will steer the fundamental research needed to develop and demonstrate scalable low-cost full-field optical metrology based on Reflectance Transformation Imaging (RTI) to support the data driven manufacture of large-volume surfaces underpinned with local metric uncertainty verification. The outcome will be validated direct optical surface measurement to unprecedented levels of accuracy across the wide variety of surface materials, forms and optical finishes that characterise advanced multi-material aerostructures. In parallel it will help inform the design of the manufacturing spaces and embedded facilities necessary to enable agile manufacture of next generation wing products in the emerging Fly Zero strategy.
Close working with partners Airbus, NCC and Taraz Metrology against industry use cases to deliver demonstrators of the developed technologies will open opportunities to extend capabilities arising from our research into other sectors where manufacture of cutting-edge high-performance digitally engineered surfaces are central to success. Examples include wind energy, shipbuilding, and onsite fabrication.
Challenging this activity are existing large volume metrology systems and deployments failing to achieve diverse engineering requirements; being too costly or needing deployments that disrupt or stop the manufacturing process. For current products metrology activities in aircraft wing manufacture are largely turn-key and consume over 25% of Airbus production time. In a systems paradigm that mirrors satellite navigation data and its now ubiquitous reliance for in-car and mobile phone navigation, improvement in productivity and flexibility to support new processes requires richer trustworthy spatial data from systems that are embedded into manufacturing infrastructure. Whilst capable systems are available at small to medium volumes and with innovation funding will evolve into industrial sensor networks, a research and technology gap in large-volume marker less surface metrology limits opportunity. Addressing the "tools to support the verification of models, metrology in manufacturing" theme of this EPSRC call, our proposal seeks to close the gap.
Our vision is to embed low-cost Reflectance Transformation Imaging guided by virtual optical metrology instrument models into factory spaces to achieve accuracies of the order of a few micrometres over areas of several tens of square metres. Airbus supports the PI through an REng/Airbus Chair in Large-Volume Metrology enabling R&T collaboration and access to specialists including manufacturing architects who design the digital factories of the future. Together we have co-created this proposal and will steer the fundamental research needed to develop and demonstrate scalable low-cost full-field optical metrology based on Reflectance Transformation Imaging (RTI) to support the data driven manufacture of large-volume surfaces underpinned with local metric uncertainty verification. The outcome will be validated direct optical surface measurement to unprecedented levels of accuracy across the wide variety of surface materials, forms and optical finishes that characterise advanced multi-material aerostructures. In parallel it will help inform the design of the manufacturing spaces and embedded facilities necessary to enable agile manufacture of next generation wing products in the emerging Fly Zero strategy.
Close working with partners Airbus, NCC and Taraz Metrology against industry use cases to deliver demonstrators of the developed technologies will open opportunities to extend capabilities arising from our research into other sectors where manufacture of cutting-edge high-performance digitally engineered surfaces are central to success. Examples include wind energy, shipbuilding, and onsite fabrication.
Publications
Mojtaba Ahmadiehkhanesar
(2024)
Enhancing single camera calibration results using artificial bee colony optimisation within a virtual environment
| Title | Illumination Rib |
| Description | In order to capture data to apply Reflectance Transformation Imaging to a series of images, multiple LEDs have to be positioned in precise and accurate locations. The traditional method was to use a dome structure but this is not practical with the large structures in this project. A rib structure which can be placed on the end of a robot arm has been designed and constructed for this purpose. The design, which consists of 6 LEDs mounted on specially designed, 3D printed supports, are held together with an acrylic structure. This is fixed to the robot end effector with a specially designed mount. |
| Type Of Material | Improvements to research infrastructure |
| Year Produced | 2024 |
| Provided To Others? | No |
| Impact | The Kuka iiwa robot, with the rib structure fixed on the end is manoeuvred into different locations allowing the LEDs to be positioned around the object of interest. The robot set up to be changed so that the position and number of LEDs can be varied allowing the optimum setup for the object's shape and surface reflectance. |
| Title | Surface Normal algorithm |
| Description | Matlab algorithm to calculate surface normals from monochromatic images and LED coordinates. The algorithm takes into account an ambient lighting correction and a white card correction. These corrections compensate for various physical factors that influence the quality of metric surface normals. |
| Type Of Material | Computer model/algorithm |
| Year Produced | 2024 |
| Provided To Others? | No |
| Impact | The accuracy of the metric surface normals generated by this code is improved allowing for greater confidence in the results, a vital step if this method were to be developed further for industry. The speed of the algorithm has been improved allowing for potential real time processing of images as they are being captured. |
| Title | Test object datasets |
| Description | Imaging sets for test objects including: aerospace fastener plate, plaster ceiling rose, Aluminium Bessel plate, 3D printed test objects (ramp, star, towers). Point clouds captured with AS1 scanner: aerospace fastener plate, plaster ceiling rose, Aluminium Bessel plate, 3D printed test objects (ramp, star, towers) |
| Type Of Material | Data analysis technique |
| Year Produced | 2024 |
| Provided To Others? | No |
| Impact | Images of the test objects have been captured for multiple setups to identify optimum arrangements for LED locations and camera settings. The point cloud data is allowing for the development of a novel method to compare the surface normals generated from the images with those from the point cloud. This will allow the accuracy of the data to be verified. |
| Description | Airbus Broughton Fastener Metrology |
| Organisation | Airbus Group |
| Department | Airbus Operations |
| Country | United Kingdom |
| Sector | Private |
| PI Contribution | UCL has commenced imaging of aerospace realistic surfaces with a static single camera and mobile near IR light source. This work is improving our understanding of the light refelected by different surface finishes in the presence of ambient illumination. This work is fundamental to the project and its capability to meet challenging aerospace engineering requirements. |
| Collaborator Contribution | Airbus Broughton has provided the joint UCL/Nottingham academic team with a reference object manufacutred from coated aerospace grade aluminium and fitted with a matrix of representative fastners of varying sizes. The heads of these fasterners have been deliiberatly miss-aligned and mounted at sub-surface levels that are indicative of the types of variation that might occur in a manufacturing process. The optical finishes and dimensions of the components on the reference object match those in current aerospace manufacture and provide an ideal starting point for the fundamental robodome imaging system design. |
| Impact | There are no formal outputs or outcomes yet from this collaboration. |
| Start Year | 2024 |
| Description | Demonstration as part of UKRI Funded Delta Aerospace Technologies project Quarterly Review Meeting |
| Form Of Engagement Activity | A formal working group, expert panel or dialogue |
| Part Of Official Scheme? | No |
| Geographic Reach | National |
| Primary Audience | Industry/Business |
| Results and Impact | UCL hosted a quarterly review meeting for the AIT funded Delta project., The meeting comprised researchers, portfolio managers and industrial professionals from UKRI, Airbus, University of Shefield, AMRC Wales, STFC Daresbury Lab and Loughborough University. Hannah Corcoran, Research fellow on the Robodome project gave a demonstration as part of the wider context of surface digitalisation for aircraft manufacture. Presented material about the Robodome project as an exemplar of low TRL research moving towards higher TRL with the potential for industrialisation. As a result the sensor will take an active role as one of a suite of measurment devices for an ATI follow on project bid for which an EOI was submitted to UKRI in late Feb of 2025. |
| Year(s) Of Engagement Activity | 2025 |
| Description | EPSRC visit to UCl HereEast |
| Form Of Engagement Activity | Participation in an open day or visit at my research institution |
| Part Of Official Scheme? | No |
| Geographic Reach | National |
| Primary Audience | Supporters |
| Results and Impact | An EPSRC visit to UCL HereEast as part of information exchange between EPSRC - built environment portfolio. , UCL researchers and UCL senior management |
| Year(s) Of Engagement Activity | 2025 |
| Description | School visit for Festival of Engineering |
| Form Of Engagement Activity | Participation in an open day or visit at my research institution |
| Part Of Official Scheme? | No |
| Geographic Reach | National |
| Primary Audience | Schools |
| Results and Impact | The Festival of Engineering (celebrating 150 years of engineering at UCL) was celebrated over a week with activities across campus. 50 local school children with a particular focus on STEM visited the laboratory for a morning. We provided a hands on demonstration of both a snake robot and drones, both of which could potentially be deployed in the Robodome project as a source of illumination. |
| Year(s) Of Engagement Activity | 2024 |
| URL | https://www.ucl.ac.uk/news/2024/jul/festival-celebrates-engineers-helping-solve-some-worlds-greatest... |
| Description | UCL Festival of Engineering |
| Form Of Engagement Activity | Participation in an open day or visit at my research institution |
| Part Of Official Scheme? | No |
| Geographic Reach | Regional |
| Primary Audience | Schools |
| Results and Impact | The UCL Festival of Engineering was a one week event held from 15th to 20th July 2024 to celebrate laboratory-based engineering education pioneered here at UCL and 2024 marks the 150th anniversary of the appointment of Sir Alexander Kennedy, who introduced the UK's first engineering teaching lab and changed the way engineering has been taught globally ever since. Activites at UCL HereEast were directed towards local schools to underline opportunities for STEM education for young people in East London. Our laboratory hosted 100 sixth form students and their teachers as a one day event covering sustainable engineering. Activites in our laboratory include industrial snake robot contol and drone flying centred around the future sustainable manufacture of aircraft and building infrastructure. Both drone and snake robot technologies connect with RoboDome as flexible ways of deploying the illumination sources needed for metric surface reconstruction over large volume. We were very impressed with the qualities of the visiting young people. Images of the day were included in the wider covertage of the UCL Festival. |
| Year(s) Of Engagement Activity | 2024 |
| URL | https://www.ucl.ac.uk/news/2024/jul/festival-celebrates-engineers-helping-solve-some-worlds-greatest... |
