• DocumentCode
    596429
  • Title

    Waist mounted Pedestrian Dead-Reckoning system

  • Author

    Jaehyun Park ; Yunki Kim ; Jangmyung Lee

  • Author_Institution
    Dept. of Robot/Cognitive Convergence Res., ETRI, Daejeon, South Korea
  • fYear
    2012
  • fDate
    26-28 Nov. 2012
  • Firstpage
    335
  • Lastpage
    336
  • Abstract
    This paper proposes a waist mounted PDR(Pedestrian Dead-Reckoning) algorithm using a low cost MEMS IMU(Inertial Measurement Unit). The PDR algorithm is consist of three algorithms which are step detection, step length estimation and heading estimation. The step detection is to detect a gait of pedestrian in walking. The step length estimation is to estimate distance of walking. The heading estimation is to find direction of walking. The PDR scheme divides two methods depending on position of mounted IMU where foot or waist mainly. This paper uses waist mounted PDR for convenience of easy implementation. Peak detection and zero crossing method are used for detecting step using 3D accelerometer data. Step length estimation based on non-linear model is applied and HDR algorithm is used for estimating the heading. To verify the effectiveness of this system, real-time system is implemented and demonstrated. Experimental results show accuracy of below 3% position error.
  • Keywords
    gait analysis; inertial navigation; micromechanical devices; position measurement; MEMS IMU; heading estimation; inertial measurement unit; peak detection; step detection; step length estimation; waist mounted pedestrian dead-reckoning system; walking pedestrian gait detection; zero crossing method; Accelerometers; Compass; Estimation; Legged locomotion; Mathematical model; Robot sensing systems; Heading; IMU; PDR; Step Detection; Step Length;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Ubiquitous Robots and Ambient Intelligence (URAI), 2012 9th International Conference on
  • Conference_Location
    Daejeon
  • Print_ISBN
    978-1-4673-3111-1
  • Electronic_ISBN
    978-1-4673-3110-4
  • Type

    conf

  • DOI
    10.1109/URAI.2012.6463008
  • Filename
    6463008