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English(EN) NAViLoss: An Underwater Navigation-Aware Dual-Residual Objective for Physics-Consistent Learning

新的NAViLoss目标函数改进了水下航行器速度估计

作者 PulseAugur 编辑部 · [2 个来源] ·

研究人员开发了NAViLoss，这是一种新颖的目标函数，旨在提高水下航行器速度估计的准确性和鲁棒性。该方法通过结合物理一致性和不确定性感知原则，解决了当前基于学习方法的局限性。NAViLoss联合惩罚导航状态和DVL测量域中的估计误差，同时自适应机制调节测量不确定性。当集成到DeepONet架构中时，由此产生的NAVi-DeepONet模型在现有方法的基础上，速度估计准确率提高了44%，这在大量真实世界AUV实验数据上得到了证明。 AI

影响 这项研究可能带来更准确、更可靠的自主水下航行器导航。

排序理由 该集群描述了一篇arXiv论文中提出的新目标函数和模型。[lever_c_demoted from research: ic=1 ai=1.0]

在 arXiv cs.LG 阅读 →

AI 生成摘要 · Google Gemini · 来自 2 个来源。 我们如何撰写摘要 →

新的NAViLoss目标函数改进了水下航行器速度估计

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该集群描述了一篇arXiv论文中提出的新目标函数和模型。[lever_c_demoted from research: ic=1 ai=1.0]
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报道来源 [2]

  1. arXiv cs.LG TIER_1 English(EN) · Arup Kumar Sahoo, Itzik Klein ·

    NAViLoss：一种水下导航感知双残差目标，用于物理一致性学习

    arXiv:2610.09690v1 Announce Type: cross Abstract: Autonomous underwater vehicles (AUVs) commonly rely on inertial navigation systems (INS) aided by Doppler velocity logs (DVLs) for reliable underwater navigation. Accurate DVL velocity estimation is therefore essential for success…

  2. Hugging Face Daily Papers TIER_1 English(EN) ·

    NAViLoss：一种水下导航感知双残差物理一致性学习目标

    Autonomous underwater vehicles (AUVs) commonly rely on inertial navigation systems (INS) aided by Doppler velocity logs (DVLs) for reliable underwater navigation. Accurate DVL velocity estimation is therefore essential for successful operation. Recent learning-based methods have …

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