arXiv 2506.151262025-06-18cs.RO

VIMS：水下环境中的视觉-惯性-磁-声纳SLAM系统

VIMS: A Visual-Inertial-Magnetic-Sonar SLAM System in Underwater Environments

Key Laboratory of Ocean Observation-Imaging Testbed of Zhejiang Province, Zhejiang University（浙江省海洋观测-成像测试床重点实验室，浙江大学）；Interdisciplinary Student Training Platform for Marine areas, Zhejiang University（海洋领域交叉人才培养平台，浙江大学）；Department of Electronic and Computer Engineering, The Hong Kong University of Science and Technology（电子与计算机工程系，香港科技大学）；The Institute of Deep-Sea Science and Engineering, Chinese Academy of Sciences（深海科学与工程研究院，中国科学院）

Bingbing Zhang, Huan Yin, Shuo Liu, Fumin Zhang, Wen Xu

备注：: This work has been accepted for publication at the IEEE/RSJ International Conference on Intelligent Robots and Systems (IROS 2025)

阅读 PDF

arXiv 页面 ↗HTML 原文 ↗

AI总结：

VIMS是一种融合视觉、惯性、磁和声纳传感器的水下SLAM系统，通过声纳改进尺度估计、磁签名实现位置识别，显著提升水下状态估计的鲁棒性和准确性。

摘要：

在本研究中，我们提出了一种新颖的同时定位与地图构建（SLAM）系统VIMS，专为水下导航设计。传统的视觉-惯性状态估计器在感知退化的水下环境中面临重大实际挑战，特别是在尺度估计和回环检测方面。为解决这些问题，我们首先提出利用低成本单波束声纳来改进尺度估计。然后，VIMS集成高采样率磁力计，通过利用经济型磁场线圈产生的磁签名进行位置识别。在此基础上，开发了一种用于视觉-磁位置识别的分层方案，实现鲁棒的回环闭合。此外，VIMS在局部特征跟踪和基于描述子的回环闭合之间取得平衡，避免给前端增加额外计算负担。实验结果突显了所提出的VIMS的有效性，展示了在水下环境中状态估计鲁棒性和准确性的显著提升。

英文摘要：

In this study, we present a novel simultaneous localization and mapping (SLAM) system, VIMS, designed for underwater navigation. Conventional visual-inertial state estimators encounter significant practical challenges in perceptually degraded underwater environments, particularly in scale estimation and loop closing. To address these issues, we first propose leveraging a low-cost single-beam sonar to improve scale estimation. Then, VIMS integrates a high-sampling-rate magnetometer for place recognition by utilizing magnetic signatures generated by an economical magnetic field coil. Building on this, a hierarchical scheme is developed for visual-magnetic place recognition, enabling robust loop closure. Furthermore, VIMS achieves a balance between local feature tracking and descriptor-based loop closing, avoiding additional computational burden on the front end. Experimental results highlight the efficacy of the proposed VIMS, demonstrating significant improvements in both the robustness and accuracy of state estimation within underwater environments.

机构、总结、中文摘要均由AI分析而来，可能存在错误，请以论文正文为准。