Modelling our way out of a featureless correspondence problem for automatic calibration of laser stripe mapping systems
Modelling our way out of a featureless correspondence problem for automatic calibration of laser stripe mapping systems
This paper discusses a problem in predicting observations for laser stripe mapping systems that is akin to the correspondence problem for stereo imagery and structure from motion. Solving this problem is essential for allowing robust, efficient, featureless calibration of laser stripe extrinsic parameters using ordinary mapping data, similar to a bundle adjustment and referred to here as an automatic calibration. Such a calibration is important for laser stripe systems to calibrate them in-situ using natural scenes without additional hardware or calibration routines. We propose a simple modelling approach that ensures single predictions are made per observation and we highlight the implications for the design of laser stripe systems that would make simple laser line extraction algorithms more robust. We present the results of an automatic calibration using this modelling approach for simulated observations of entirely featureless terrain by a laser stripe mapping system; proving the concept of a robust, efficient, featureless, automatic calibration of laser stripe extrinsics.
bundle adjustment, calibration, correspondence problem, design, extrinsics, featureless, laser stripe, seafloor mapping, structured light, underwater robotics
Stanley, David
c8f86333-0eeb-42df-9e63-5cbc0b115514
Bodenmann, Adrian
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Massot Campos, Miguel
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Thornton, Blair
8293beb5-c083-47e3-b5f0-d9c3cee14be9
24 April 2023
Stanley, David
c8f86333-0eeb-42df-9e63-5cbc0b115514
Bodenmann, Adrian
070a668f-cc2f-402a-844e-cdf207b24f50
Massot Campos, Miguel
a55d7b32-c097-4adf-9483-16bbf07f9120
Thornton, Blair
8293beb5-c083-47e3-b5f0-d9c3cee14be9
Stanley, David, Bodenmann, Adrian, Massot Campos, Miguel and Thornton, Blair
(2023)
Modelling our way out of a featureless correspondence problem for automatic calibration of laser stripe mapping systems.
In 2023 IEEE International Symposium on Underwater Technology, UT 2023.
IEEE.
8 pp
.
(doi:10.1109/UT49729.2023.10103452).
Record type:
Conference or Workshop Item
(Paper)
Abstract
This paper discusses a problem in predicting observations for laser stripe mapping systems that is akin to the correspondence problem for stereo imagery and structure from motion. Solving this problem is essential for allowing robust, efficient, featureless calibration of laser stripe extrinsic parameters using ordinary mapping data, similar to a bundle adjustment and referred to here as an automatic calibration. Such a calibration is important for laser stripe systems to calibrate them in-situ using natural scenes without additional hardware or calibration routines. We propose a simple modelling approach that ensures single predictions are made per observation and we highlight the implications for the design of laser stripe systems that would make simple laser line extraction algorithms more robust. We present the results of an automatic calibration using this modelling approach for simulated observations of entirely featureless terrain by a laser stripe mapping system; proving the concept of a robust, efficient, featureless, automatic calibration of laser stripe extrinsics.
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Accepted/In Press date: 23 December 2022
Published date: 24 April 2023
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Publisher Copyright:
© 2023 IEEE.
Venue - Dates:
IEEE International Symposium on Underwater Technology 2023, ISS Confernce Hall 'Haricot' , Tokyo, Japan, 2023-03-06 - 2023-03-09
Keywords:
bundle adjustment, calibration, correspondence problem, design, extrinsics, featureless, laser stripe, seafloor mapping, structured light, underwater robotics
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Local EPrints ID: 475406
URI: http://eprints.soton.ac.uk/id/eprint/475406
PURE UUID: dad6c1bc-c654-47e2-8206-644fa194cb6a
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Date deposited: 17 Mar 2023 17:31
Last modified: 18 Mar 2024 03:50
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Author:
David Stanley
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