aiqbench analysis
This research introduces MI-SLAM systems that achieve robust indoor positioning using only low-cost IMUs and magnetometers, eliminating the need for visual or wheel-based odometry. By leveraging spatially inhomogeneous magnetic fields, these algorithms provide bounded error mapping suitable for environments where GNSS is unavailable, such as mine rescue operations. The approach represents a significant advancement in sensor fusion for robotics and autonomous navigation in GPS-denied scenarios.
MI-SLAM: Magnetic Inertial SLAM Systems
arXiv:2512.10128v4 Announce Type: replace Abstract: 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.
Abstract: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.
Robotics (cs.RO); Signal Processing (eess.SP)
arXiv:2512.10128 [cs.RO]
(or arXiv:2512.10128v4 [cs.RO] for this version)
https://doi.org/10.48550/arXiv.2512.10128 Focus to learn more arXiv-issued DOI via DataCite
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