Global indoor self-localization based on the ambient magnetic field
ABSTRACT There is evidence that animals utilize local anomalities of Earth’s magnetic field not just for orientation detection but also for true navigation, i.e., some animals are not only able to detect the direction of Earth’s magnetic field (compass heading), they are able to derive positional information from local cues arising from the local anomalities of Earth’s magnetic field. Similarly to Earth’s non-constant magnetic field, the magnetic field inside buildings can be highly non-uniform. The magnetic field fluctuations inside buildings arise from both natural and man-made sources, such as steel and reinforced concrete structures, electric power systems, electric and electronic appliances, and industrial devices. Assuming that the anomalities of the magnetic field inside a building are nearly static and they have sufficient local variability, the anomalies provide a unique magnetic fingerprint that can be utilized in global self-localization. Based on the evidence presented in this article it can be argued that this hypothesis is valid. In this article, a Monte Carlo Localization (MCL) technique based on the above hypothesis is proposed. The feasibility of the technique is demonstrated by presenting a series of global self-localization experiments conducted in four arbitrarily selected buildings, including a hospital. The experiment setup consists of a mobile robot instrumented with a 3-axis magnetometer and a computer. In addition to global robot self-localization experiments, successful person self-localization experiments were also conducted by using a wireless, wearable magnetometer. The reported experiments suggest that the ambient magnetic field may remain sufficiently stable for longer periods of time giving support for self-localization techniques utilizing the local deviations of the magnetic field.
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ABSTRACT: The need for accurate indoor localization increases as we get used to accessible outdoor localization, and the number of applications depending on localization grows. Indoor localization is challenging because of frequent line of sight obstructions and dynamic changes in the environment. Magnetometers can be found in many modern electronic devices and provide a simple way to measure the geomagnetic field intensity. Due to distortions in this magnetic field, these measurements often provide enough information to enable identification of a location using pattern matching. We show the feasibility of using these magnetic field intensity measurements in localization and SLAM applications. Our SLAM system of choice is the biologically inspired RatSLAM, as it allows pattern matching as scene recognition. We demonstrate a number of experiments in various environments, including a suburban house and a university lab. We conclude that geomagnetic localization and SLAM are feasible in environments with many distortions in the magnetic field. Such locations are easier to identify than locations with little distortions, which will have the same pattern of magnetic field over larger areas.International Journal On Advances in Systems and Measurements. 01/2014; 7(1&2):44-56.
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ABSTRACT: Indoor navigation in emergency scenarios poses a challenge to evacuation and emergency support, especially for injured or physically encumbered individuals. Navigation systems must be lightweight, easy to use, and provide robust localization and accurate navigation instructions in adverse conditions. To address this challenge, we combine magnetic location tracking with an optical character recognition (OCR) and eye gaze based method to recognize door plates and position related text to provide more robust localization. In contrast to typical wireless or sensor based tracking, our fused system can be used in low-lighting, smoke, and areas without power or wireless connectivity. Eye gaze tracking is also used to improve time to localization and accuracy of the OCR algorithm. Once localized, navigation instructions are transmitted directly into the user's immediate field of view via head mounted display (HMD). Additionally, setting up the system is simple and can be done with minimal calibration, requiring only a walk-through of the environment and numerical annotation of a 2D area map. We conduct an evaluation for the magnetic and OCR systems individually to evaluate feasibility for use in the fused framework.2014 IEEE International Conference on Pervasive Computing and Communication Workshops (PERCOM WORKSHOPS); 03/2014
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ABSTRACT: The dependence of proposed pedestrian navigation solutions on a dedicated infrastructure is a limiting factor to the deployment of location based services. Consequently self-contained Pedestrian Dead-Reckoning (PDR) approaches are gaining interest for autonomous navigation. Even if the quality of low cost inertial sensors and magnetometers has strongly improved, processing noisy sensor signals combined with high hand dynamics remains a challenge. Estimating accurate attitude angles for achieving long term positioning accuracy is targeted in this work. A new Magnetic, Acceleration fields and GYroscope Quaternion (MAGYQ)-based attitude angles estimation filter is proposed and demonstrated with handheld sensors. It benefits from a gyroscope signal modelling in the quaternion set and two new opportunistic updates: magnetic angular rate update (MARU) and acceleration gradient update (AGU). MAGYQ filter performances are assessed indoors, outdoors, with dynamic and static motion conditions. The heading error, using only the inertial solution, is found to be less than 10° after 1.5 km walking. The performance is also evaluated in the positioning domain with trajectories computed following a PDR strategy.Sensors 12/2014; 14:22864-22890. · 2.05 Impact Factor