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Application of an Improved Underwater SLAM Algorithm for Oil Pipeline Localization and Environmental Reconstruction

Author(s)

Qiang Wen

Affiliation(s)

Harbin Institute of Petroleum, Harbin, Heilongjiang, China

Abstract

With the increasing development of marine oil resources, precise localization of oil pipelines and underwater environmental reconstruction are critical for ensuring operational safety and efficiency. This study focuses on enhancing the underwater simultaneous localization and mapping (SLAM) algorithm to improve its performance in oil pipeline localization and complex underwater environment reconstruction. By integrating multi-source sensor data, including sonar and visual sensors, and introducing optimized data association and filtering algorithms, we enhance traditional underwater SLAM techniques. The research begins with preprocessing sensor data to eliminate noise interference, followed by real-time data processing using the improved algorithm to achieve accurate self-localization of underwater vehicles and the construction of surrounding environmental maps, particularly for precise identification and labeling of oil pipeline locations. The results demonstrate significant improvements in localization accuracy and environmental reconstruction completeness with the enhanced underwater SLAM algorithm, effectively meeting the practical needs of oil pipeline localization and underwater environmental construction, thereby providing more reliable technical support for marine oil engineering operations.

Keywords

Underwater SLAM; Oil Pipeline Localization; Environmental Reconstruction; Multi-Source Sensor Fusion; Data Processing

References

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