Human-interactive Mapping Method for Indoor Magnetic Based on Low-cost MARG Sensors

Abstract

Indoor magnetic map (IMM) based on magnetic field fluctuations can be used in map assisted indoor positioning and navigation, etc. However, many IMM mapping solutions are time-consuming, labor-intensive, and high-cost, which limit the development and application of IMM. To solve the issues of accuracy, efficiency, and cost of IMM mapping collaboratively, we absorbed the idea of simultaneous localization and mapping (SLAM) method, and proposed a human-interactive mapping method of IMM based on the low-cost magnetometer, accelerometer, and rate gyro, i.e., MARG sensors. First, we defined IMM as the structured data set with a series of position stamps and magnetic field fluctuations. Then, we proposed the concept of general sensory calibration source (GSCS) and related metrics for human-interactive activities which provide virtual information to eliminate the time-accumulated error of position stamps and assist in obtaining stable magnetic field fluctuations. Finally, we conduct a series of experiments to verify the performance of the proposed method. The test results show that the proposed method can not only meet the requirements of mapping accuracy but also significantly improve mapping efficiency and reduce mapping cost, which is superior to other state-of-the-art algorithms. Specifically, the significant results are as follows: the mapping accuracy is about 0.31 m, and the mapping efficiency is 1800 m$^2$ per hour, and the cost of the main module of IMM mapping does not exceed U.S. $10.