arXiv 2512.101282026-08-27cs.ROeess.SP

利用低成本传感器的惯性磁力SLAM系统

MI-SLAM: Magnetic Inertial SLAM Systems

Dept. of Electrical Engineering and Computer Science, KTH Royal Institute of Technology（电气工程与计算机科学系，皇家理工学院）；Dept. of Electrical Engineering, Linköping University（电气工程系，林波大学）；Dept.of Electrical Engineering and Computer Science, KTH Royal Institute of Technology（电气工程与计算机科学系，皇家理工学院）；Division of Underwater Technology, Swedish Defence Research Agency (FOI)（水下技术 division，瑞典国防研究机构（FOI））

Chuan Huang, Gustaf Hendeby, Isaac Skog

备注：: Reduce the number of magnetometers involved to 7

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AI总结：

本文提出基于磁力辅助惯性导航的松耦合和紧耦合惯性磁力SLAM系统，利用低成本传感器实现高精度定位，实验表明紧耦合系统在多数场景下定位误差更小。

摘要：

空间非均匀磁场均能提供有价值的非视觉定位信息。在利用该信息的系统中，基于磁场的同步定位与建图系统尤为吸引人。这些系统同时执行定位和磁场映射任务，并在已访问区域内具有有界的定位误差。然而，最先进的磁场SLAM方法通常需要低漂移惯性数据，如视觉惯性、轮式编码器或步行死 reckoning技术。为了解决这一限制，本文提出松耦合和紧耦合的惯性磁力SLAM（IM-SLAM）系统，仅使用低成本传感器：惯性测量单元（IMU）、30个磁力计和气压计。两种系统均基于磁力辅助惯性导航系统（INS）并使用误差状态卡尔曼滤波器进行状态估计。两种系统的主要区别在于导航状态估计是单步还是双步。这些系统在具有多层结构的真实室内环境中进行了评估。实验结果表明，在大多数场景中，紧耦合IM-SLAM系统比松耦合系统具有更小的定位误差，典型误差在每100米行驶中为米级。这些结果证明了使用低成本传感器开发完整3D IM-SLAM系统的可行性。所提出系统的潜在应用是为应急响应人员的定位。

英文摘要：

Spatially inhomogeneous magnetic fields offer a valuable, non-visual information source for positioning. Among systems leveraging this, magnetic field-based simultaneous localization and mapping (SLAM) systems are particularly attractive. These systems execute positioning and magnetic field mapping tasks simultaneously, and they have bounded positioning error within previously visited regions. However, state-of-the-art magnetic-field SLAM methods typically require low-drift odometry data provided by visual odometry, a wheel encoder, or pedestrian dead-reckoning technology, which may not be available under certain situations. To address this limitation, this work proposes two magnetic inertial SLAM (MI-SLAM) systems --- a loosely coupled version and a tightly coupled version --- that rely solely on low-cost sensors: an inertial measurement unit (IMU) and seven magnetometers. Both systems use a magnetic field aided inertial navigation system (MAINS) to obtain odometry. The key difference between the two systems is whether the navigation state estimation is done in one or two steps. These systems are evaluated in real-world indoor environments with multi-floor structures. The proposed MI-SLAM systems outperform the state-of-the-art magnetic-inertial odometry system, MAINS, achieving a positioning RMSE below 1 meter on a trajectory lasting approximately 200 seconds. A potential application of the proposed systems is for the positioning of emergency response officers in mine or fire rescue operations, where one cannot rely on a GNSS or visual-based localization system.

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