Fast and Deterministic Underwater Point Cloud Registration for Multibeam Echo Sounder Data

Investigating underwater environments using Multi-Beam Echo Sounder (MBES) point cloud registration technology is a critical yet underdeveloped area in oceanographic research. This paper presents a fast, deterministic Branch-and-Bound (BnB) method with four degrees of freedom, which combines Inertial Measurement Unit (IMU) data with MBES point cloud data for precise registration. Given the prevalence of outliers and noise in underwater acoustic measurements, the BnB method is employed to provide globally deterministic solutions. However, due to the exponential convergence speed of the BnB method with respect to the dimensionality of the solution space, searching within a six-degree-of-freedom parameter space (three rotational and three translational degrees of freedom) can be extremely time-consuming. To this end, the Z-axis of the point cloud is aligned with the gravitational direction of the IMU, reducing the rotational degrees of freedom from three to one, specifically concerning yaw. Additionally, an outlier exclusion strategy is introduced to eliminate mismatches, significantly reducing the number of key-point correspondences and thereby improving registration efficiency. Experiments conducted on both public and real-world lake datasets demonstrate that the proposed method achieves a favorable balance between speed and accuracy, outperforming other tested methods and meeting the demands of contemporary research.

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Publication Details

Journal
Journal of Marine Science and Engineering
Published
2024-12-28
DOI
https://doi.org/10.3390/jmse13010026
Primary Topic
Robotics and Sensor-Based Localization
Type
article
Field-Weighted Citation Impact
0.00

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article

Fast and Deterministic Underwater Point Cloud Registration for Multibeam Echo Sounder Data

Lan Cheng, Chun Cao, Feihu Zhang, Tingfeng Tan et al.
Journal of Marine Science and Engineering
Robotics and Sensor-Based Localization
article

Fast and Deterministic Underwater Point Cloud Registration for Multibeam Echo Sounder Data

Lan Cheng, Chun Cao, Feihu Zhang, Tingfeng Tan, Liang Zhao
article en

Abstract

Investigating underwater environments using Multi-Beam Echo Sounder (MBES) point cloud registration technology is a critical yet underdeveloped area in oceanographic research. This paper presents a fast, deterministic Branch-and-Bound (BnB) method with four degrees of freedom, which combines Inertial Measurement Unit (IMU) data with MBES point cloud data for precise registration. Given the prevalence of outliers and noise in underwater acoustic measurements, the BnB method is employed to provide globally deterministic solutions. However, due to the exponential convergence speed of the BnB method with respect to the dimensionality of the solution space, searching within a six-degree-of-freedom parameter space (three rotational and three translational degrees of freedom) can be extremely time-consuming. To this end, the Z-axis of the point cloud is aligned with the gravitational direction of the IMU, reducing the rotational degrees of freedom from three to one, specifically concerning yaw. Additionally, an outlier exclusion strategy is introduced to eliminate mismatches, significantly reducing the number of key-point correspondences and thereby improving registration efficiency. Experiments conducted on both public and real-world lake datasets demonstrate that the proposed method achieves a favorable balance between speed and accuracy, outperforming other tested methods and meeting the demands of contemporary research.

Journal of Marine Science and EngineeringVol. 13(1)
Northwestern Polytechnical University (CN), Taiyuan University of Technology (CN)
National Natural Science Foundation of China, Fundamental Research Funds for the Central Universities
Reduced inequalities
Openalex Percentile: Top 58%
Robotics and Sensor-Based Localization
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Fast and Deterministic Underwater Point Cloud Registration for Multibeam Echo Sounder Data — Lan Cheng, Chun Cao, et al. · Journal of Marine Science and Engineering (2024) | TGRS Research Map | TGRS