水下无人系统学报2025，Vol.33Issue(1)：99-107,9.DOI:10.11993/j.issn.2096-3920.2024-0061
基于视觉-惯性-压力融合的水下定位方法
Underwater Positioning Method Based on Vision-Inertia-Pressure Fusion
摘要
Abstract
In underwater unstructured environments,robots face difficulties in relying on external base stations for localization.Therefore,autonomous localization using multi-sensor fusion has significant application value in such settings.This paper aimed to address issues such as poor stability in visual localization and substantial drift in inertial navigation within underwater multi-sensor fusion localization and proposed a tightly integrated multi-sensor fusion localization method that combined visual,inertial,and pressure sensors.By utilizing graph optimization techniques for multi-sensor fusion and identifying errors in visual-inertial data based on depth information,the quality of the fused data was enhanced.To address drift and localization loss during the fusion localization process,a depth sensor was employed for weight allocation to provide more detailed system initialization.Additionally,closed-loop detection and relocalization methods were introduced to effectively mitigate drift and localization loss.Experimental validation demonstrates that the proposed fusion localization algorithm improves accuracy by 48.4%compared to visual-inertial fusion localization methods,achieving superior precision and robustness.The actual positioning accuracy can reach the centimetre level.关键词
水下定位/多传感器融合定位/图优化Key words
underwater localization/multi-sensor fusion localization/graph optimization分类
军事科技引用本文复制引用
张箭,胡桥,夏寅,石麟,李洋阳..基于视觉-惯性-压力融合的水下定位方法[J].水下无人系统学报,2025,33(1):99-107,9.基金项目
陕西省秦创原队伍建设项目资助(S2022-ZC-QCYK-0178). （S2022-ZC-QCYK-0178）
