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Dimensional uncertainty quantification for laser-scanning-based underwater 3D reconstructions

Dimensional uncertainty quantification for laser-scanning-based underwater 3D reconstructions
Dimensional uncertainty quantification for laser-scanning-based underwater 3D reconstructions

High-resolution seafloor mapping from autonomous underwater vehicles (AUVs) or remotely operated vehicles is an important tool for assessing benthic ecosystems and infrastructure, which is increasingly becoming routine. While single surveys show a snapshot in time of the state of such environments, repeat surveys can identify how these change over time. To gauge whether changes are statistically significant, it is necessary to quantify the uncertainty of such 3D reconstructions; however, most 3D reconstruction methods do not provide any such measure. While there are various sources of uncertainty when reconstructing seafloor terrain data from structured light surveys, this research focusses on the contribution from the line laser pose uncertainty to the dimensional uncertainty of laser-scanning-based underwater 3D reconstructions. A Monte Carlobased approach is used to model the laser fan pose uncertainty from stereo images of the laser line projection acquired from various distances from the seafloor. The method is demonstrated on data acquired at the Southern Hydrate Ridge off the coast of Oregon with the SeaXerocks 3 mapping device deployed with the AE2000f AUV.

AUV, laser scanning, uncertainty, underwater 3D mapping
IEEE
Bodenmann, Adrian
070a668f-cc2f-402a-844e-cdf207b24f50
Massot-Campos, Miquel
a55d7b32-c097-4adf-9483-16bbf07f9120
Thornton, Blair
8293beb5-c083-47e3-b5f0-d9c3cee14be9
Bodenmann, Adrian
070a668f-cc2f-402a-844e-cdf207b24f50
Massot-Campos, Miquel
a55d7b32-c097-4adf-9483-16bbf07f9120
Thornton, Blair
8293beb5-c083-47e3-b5f0-d9c3cee14be9

Bodenmann, Adrian, Massot-Campos, Miquel and Thornton, Blair (2025) Dimensional uncertainty quantification for laser-scanning-based underwater 3D reconstructions. In 2025 IEEE Underwater Technology, UT 2025. IEEE. 4 pp . (doi:10.1109/UT61067.2025.10947277).

Record type: Conference or Workshop Item (Paper)

Abstract

High-resolution seafloor mapping from autonomous underwater vehicles (AUVs) or remotely operated vehicles is an important tool for assessing benthic ecosystems and infrastructure, which is increasingly becoming routine. While single surveys show a snapshot in time of the state of such environments, repeat surveys can identify how these change over time. To gauge whether changes are statistically significant, it is necessary to quantify the uncertainty of such 3D reconstructions; however, most 3D reconstruction methods do not provide any such measure. While there are various sources of uncertainty when reconstructing seafloor terrain data from structured light surveys, this research focusses on the contribution from the line laser pose uncertainty to the dimensional uncertainty of laser-scanning-based underwater 3D reconstructions. A Monte Carlobased approach is used to model the laser fan pose uncertainty from stereo images of the laser line projection acquired from various distances from the seafloor. The method is demonstrated on data acquired at the Southern Hydrate Ridge off the coast of Oregon with the SeaXerocks 3 mapping device deployed with the AE2000f AUV.

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More information

Published date: 8 April 2025
Venue - Dates: 2025 IEEE Underwater Technology, UT 2025, , Taipei, Taiwan, 2025-03-02 - 2025-03-05
Keywords: AUV, laser scanning, uncertainty, underwater 3D mapping

Identifiers

Local EPrints ID: 501923
URI: http://eprints.soton.ac.uk/id/eprint/501923
PURE UUID: 3acd8a14-c788-47e2-aad7-532e350bc766
ORCID for Adrian Bodenmann: ORCID iD orcid.org/0000-0002-3195-0602
ORCID for Miquel Massot-Campos: ORCID iD orcid.org/0000-0002-1202-0362

Catalogue record

Date deposited: 12 Jun 2025 16:33
Last modified: 04 Sep 2025 02:23

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