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AUV underwater visual guided docking based on deep learning localization algorithm
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DOI：10.1016/j.oceaneng.2026.124337.png)
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• An docking method for AUVs achieving a minimum pixel error of 6.56 is proposed. • A guiding light positioning method based on deep neural network is developed. • The lightweight GLLNet achieves a higher mAP of 71.6% with only 4.5M parameters. • A fuzzy adaptive docking control method based on PID and S-surface is improved.
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7.6K
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