Acta Geodaetica et Cartographica Sinica ›› 2022, Vol. 51 ›› Issue (1): 18-30.doi: 10.11947/j.AGCS.2022.20200251

• Geodesy and Navigation • Previous Articles     Next Articles

High-precision indoor positioning based on robust LM visual inertial odometer and pseudosatellite

YANG Gaochao1,2, WANG Qing1,2, YU Baoguo3, LIU Pengfei1,2, LI Shuang3   

  1. 1. School of Instrument Science and Engineering, Southeast University, Nanjing 210096, China;
    2. Smart City Research Institute, Southeast University, Nanjing 210096, China;
    3. State Key Laboratory of Satellite Navigation System and Equipment Techonlogy, The 54th Research Institute of China Electronics Technology Group Corporation, Shijiazhuang 050050, China
  • Received:2020-07-17 Revised:2021-11-11 Published:2022-02-15
  • Supported by:
    The National Key Research and Development Program of China (No. 2020YFD110011-01)

Abstract: Visual inertial odometer (VIO) and pseudo-satellite have been widely used in positioning indoors, but in practical applications, both approaches have their own limitations. The visual odometer depends on the actual positioning environments. Gross errors occur in environments with obvious changes in depth of field and uneven illumination, and errors will inevitably accumulate over time. However, relatively high-precision pose measurements can be obtained between adjacent frames. Due to the influence of indoor multipath, the accuracy and reliability of pseudolite indoor positioning are difficult to guarantee. To increase the reliability and stability of indoor positioning, based on the robust LM nonlinear optimization theory, this study mainly investigate indoor high-precision positioning technology approach of integrating high-precision pose measurements of VIO between adjacent frame and pseudolite. The algorithm can not only resist gross errors, but also reduce the influence of unreasonable weight settings among different sensors. Finally, the high-precision dynamic capture equipment built in the indoor environment is used to verify the proposed method. The experimental results show that the method can eliminate the cumulative error of the visual inertial odometer without relying on the loopback, and effectively improve the indoor positioning accuracy and reliability. Compared with the VIO, the positioning accuracy is improved by 59.0% and 77.5% respectively after using the improved LM algorithm for scenes 1 and 2.

Key words: visual inertial odometer, pseudosatellite, LM, robust estimation, indoor positioning

CLC Number: