Sonar-Based Simultaneous Localization and Mapping Using the Semi-Direct Method
The SLAM problem is a common challenge faced by ROVs working underwater, with the key issue being the accurate estimation of pose. In this work, we make full use of the positional information of point clouds and the surrounding pixel data. To obtain better feature extraction results in specific dire...
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| Main Authors: | , , , , |
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| Format: | Article |
| Language: | English |
| Published: |
MDPI AG
2024-12-01
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| Series: | Journal of Marine Science and Engineering |
| Subjects: | |
| Online Access: | https://www.mdpi.com/2077-1312/12/12/2234 |
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| Summary: | The SLAM problem is a common challenge faced by ROVs working underwater, with the key issue being the accurate estimation of pose. In this work, we make full use of the positional information of point clouds and the surrounding pixel data. To obtain better feature extraction results in specific directions, we propose a method that accelerates the computation of the two-dimensional SO-CFAR algorithm, with the time cost being only a very slight increase compared to the one-dimensional SO-CFAR. We develop a sonar semi-direct method, adapted from the direct method used in visual SLAM. With the initialization from the ICP algorithm, we apply this method to further refine the pose estimation. To overcome the deficiencies of sonar images, we preprocess the images and reformulate the sonar imaging model in imitation of camera imaging models, further optimizing the pose by minimizing photometric error and fully leveraging pixel information. The improved front end and the accelerated two-dimensional SO-CFAR are assessed through quantitative experiments. The performance of SLAM in large real-world environments is assessed through qualitative experiments. |
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| ISSN: | 2077-1312 |