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 because they can provide positioning information and build a magnetic field map on the fly. Moreover, they have bounded error within mapped regions. However, state-of-the-art methods typically require low-drift odometry data provided by visual odometry or a wheel encoder, etc. This is because these systems need to minimize/reduce positioning errors while exploring, which happens when they are in unmapped regions. To address these limitations, this work proposes a loosely coupled and a tightly coupled inertial magnetic SLAM (IM-SLAM) system. The proposed systems use commonly available low-cost sensors: an inertial measurement unit (IMU), a magnetometer array, and a barometer. The use of non-visual data provides a significant advantage over visual-based systems, making it robust to low-visibility conditions. Both systems employ state-space representations, and magnetic field models on different scales. The difference lies in how they use a local and global magnetic field model. The loosely coupled system uses these models separately in two state-space models, while the tightly coupled system integrates them into one state-space model. Experiment results show that the tightly coupled IM-SLAM system achieves lower positioning errors than the loosely coupled system in most scenarios, with typical errors on the order of meters per 100 meters traveled. These results demonstrate the feasiblity of developing a full 3D IM-SLAM systems using low-cost sensors and the potential of applying these systems in emergency response scenarios such as mine/fire rescue.

翻译：空间非均匀磁场为定位提供了一种宝贵的非视觉信息源。在利用这一原理的系统中，基于磁场的同步定位与地图构建（SLAM）系统尤为引人注目，因为它能在运动过程中同时提供定位信息并构建磁场地图。此外，这类系统在地图覆盖区域内具有有界误差。然而，现有先进方法通常需要视觉里程计或轮式编码器等提供的低漂移里程计数据。这是因为这些系统在探索未测绘区域时需要最小化/减少定位误差。为解决这些局限，本文提出了一种松耦合和一种紧耦合的惯性磁SLAM（IM-SLAM）系统。所提系统使用普遍可得的低成本传感器：惯性测量单元（IMU）、磁力计阵列和气压计。非视觉数据的使用使其相比基于视觉的系统具有显著优势，能在低可见度条件下保持鲁棒性。两种系统均采用状态空间表示法，以及不同尺度的磁场模型。其差异在于对局部和全局磁场模型的使用方式：松耦合系统在两个独立的状态空间模型中分别使用这些模型，而紧耦合系统将其整合为一个状态空间模型。实验结果表明，在大多数场景中，紧耦合IM-SLAM系统的定位误差低于松耦合系统，典型误差为每行进100米米级精度。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，以及将该系统应用于矿井/火灾救援等应急响应场景的潜力。