Global Indoor self-localization based on the ambient magnetic field

University of Oulu, Department of Electrical and Information Engineering, Computer Engineering Laboratory, Erkki Koiso-Kanttilan katu 3, FIN-90014 University of Oulu, Finland
Robotics and Autonomous Systems (Impact Factor: 1.26). 10/2009; 57(10):1028-1035. DOI: 10.1016/j.robot.2009.07.018
Source: DBLP

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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    • "A second method was recently proposed for navigating using only mesured magnetic fields. A calibration phase maps all indoor magnetic field [8],[9]. Then, similarly to fingerprinting methods with WiFi receiver signal strength, magnetic anomalies are used to identify the user's location. "
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    ABSTRACT: Pedestrian Dead-Reckoning (PDR) is the prime candidate for autonomous navigation with self-contained sensors. Nevertheless with noisy sensor signals and high hand dynamics, estimating accurate attitude angles remains a challenge for achieving long term positioning accuracy. A new attitude estimation algorithm based on a quaternion parameterization directly in the state vector and two opportunistic updates, i.e. magnetic angular rate update and acceleration gradient update, is proposed. The benefit of this method is assessed both at the theoretical level and at the experimental level. The error on the heading, estimated only with the PDR navigation algorithms, is found to less than 7° after 1 km of walk.
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    • "In order to accomplish magnetic localization, we first attempted to use an already existing system called IndoorAtlas, which allows users to create and navigate indoor maps [8]. After several tests, we quickly found that this system is prone to error, and does not give direct access to raw magnetic data. "
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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.
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    • "While this is a very good approach to self-localization, the vehicle is dependent on a camera and the computation ability to process images quickly. Haverinen et al. [10] propose an excellent basis for self-localization utilizing ambient magnetic fields for indoor environments, whilst using the Monte Carlo Localization technique. Fig. 1. "
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