Auledas-Noguera, M., Liaqat, A. and Tiwari, A. (2022) Mobile robots for in-process monitoring of aircraft systems assemblies. Sensors, 22 (9). 3362. ISSN 1424-8220
Abstract
Currently, systems installed on large-scale aerospace structures are manually equipped by trained operators. To improve current methods, an automated system that ensures quality control and process adherence could be used. This work presents a mobile robot capable of autonomously inspecting aircraft systems and providing feedback to workers. The mobile robot can follow operators and localise the position of the inspection using a thermal camera and 2D lidars. While moving, a depth camera collects 3D data about the system being installed. The in-process monitoring algorithm uses this information to check if the system has been correctly installed. Finally, based on these measurements, indications are shown on a screen to provide feedback to the workers. The performance of this solution has been validated in a laboratory environment, replicating a trailing edge equipping task. During testing, the tracking and localisation systems have proven to be reliable. The in-process monitoring system was also found to provide accurate feedback to the operators. Overall, the results show that the solution is promising for industrial applications.
Metadata
Item Type: | Article |
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Authors/Creators: |
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Copyright, Publisher and Additional Information: | © 2022 by the authors. Licensee MDPI, Basel, Switzerland. This article is an open access article distributed under the terms and conditions of the Creative Commons Attribution (CC BY) license (https://creativecommons.org/licenses/by/4.0/). |
Keywords: | automatic inspection; aerospace assembly; mobile robotics; depth camera |
Dates: |
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Institution: | The University of Sheffield |
Academic Units: | The University of Sheffield > Faculty of Engineering (Sheffield) > Department of Automatic Control and Systems Engineering (Sheffield) |
Depositing User: | Symplectic Sheffield |
Date Deposited: | 17 Jun 2022 09:27 |
Last Modified: | 17 Jun 2022 09:27 |
Status: | Published |
Publisher: | MDPI AG |
Refereed: | Yes |
Identification Number: | 10.3390/s22093362 |
Related URLs: | |
Open Archives Initiative ID (OAI ID): | oai:eprints.whiterose.ac.uk:188099 |