Abstract
Deep-sea mining system is used to collect manganese nodules or other seabed mineral resources. When the deep-sea mining vehicle works, long-term localization is important to realize efficient and safe operation. This study proposes a localization algorithm which can get accurate, real-time localization results for deep-sea mining vehicle. The forward-looking sonar is used here to estimate the motion of deep-sea mining vehicle by image matching. Stable features of objects are identified from the sonar images. The 3-D point clouds of object features are generated by the geometric relationships of the sonar projection model and then used for image matching to obtain relative pose transformation for constructing the odometer. The framework of the data fusion algorithm is based on pose graph, allowing global and relative measurements of position from multiple heterogeneous sensors to be integrated together. The proposed localization algorithm is validated through the dataset acquired during sea trials in July 2021 with “Pioneer I” in the South China Sea. The results of validation show that the proposed localization algorithm can output accurate positioning results for the deep-sea mining vehicle.
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