Rugg-Gunn, D. and Aitken, J.M. orcid.org/0000-0003-4204-4020 (2022) Investigating scene visibility estimation within ORB-SLAM3. In: Pacheco-Gutierrez, S., Cryer, A., Caliskanelli, I., Tugal, H. and Skilton, R., (eds.) Towards Autonomous Robotic Systems: 23rd Annual Conference, TAROS 2022, Culham, UK, September 7–9, 2022, Proceedings. 23rd Annual Conference (TAROS 2022), 07-09 Sep 2022, Culham, UK. Lecture Notes in Computer Science, LNAI 13546 . Springer International Publishing , pp. 155-165. ISBN 9783031159077
Abstract
Scene Visibility Estimation offers a collection of metrics that give a good indication of the quality of images that are being supplied to a Visual or Visual-Inertial Simultaneous Location and Mapping algorithm. This paper will investigate the application of these metrics during switching between camera and IMU-based localisation within the popular visual-inertial ORB-SLAM3 algorithm. Application of the metrics provides more flexibility compared to a static threshold and incorporating the metrics within the switch provides a reduction in the error in positioning.
Metadata
Item Type: | Proceedings Paper |
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Authors/Creators: |
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Editors: |
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Copyright, Publisher and Additional Information: | © 2022 The Author(s), under exclusive license to Springer Nature Switzerland AG. This is an author-produced version of a paper subsequently published in Lecture Notes in Computer Science. Uploaded in accordance with the publisher's self-archiving policy. |
Keywords: | Simultaneous Localisation and Mapping; Visibility |
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: | 22 Feb 2023 15:54 |
Last Modified: | 01 Sep 2023 00:13 |
Status: | Published |
Publisher: | Springer International Publishing |
Series Name: | Lecture Notes in Computer Science |
Refereed: | Yes |
Identification Number: | 10.1007/978-3-031-15908-4_13 |
Related URLs: | |
Open Archives Initiative ID (OAI ID): | oai:eprints.whiterose.ac.uk:196548 |