• DocumentCode
    187330
  • Title

    Design and implementation of sensor data fusion for an autonomous quadrotor

  • Author

    Tailanian, Matias ; Paternain, Santiago ; Rosa, Renata ; Canetti, Rafael

  • Author_Institution
    Univ. de la Republica, Montevideo, Uruguay
  • fYear
    2014
  • fDate
    12-15 May 2014
  • Firstpage
    1431
  • Lastpage
    1436
  • Abstract
    This paper describes the design and integration of the instrumentation and sensor fusion that is used to allow the autonomous flight of a quadrotor. A comercial frame is used, a mathematical model for the quadrotor is developed and its parameters determined from the characterization of the unit. A 9 degrees of freedom Inertial Measurement Unit (IMU) equipped with a barometer is calibrated and added to the platform. Sensor fusion is done by two modified Extended Kalman Filters (EKF): one combining data provided by IMU and the other also including the information provided by GPS. A reliable estimation of the state variables is obtained. Three states representing systematic bias in the accelerometer measurements are also added to the EKF, which improves the inertial estimation of the position. A stable autonomous platform is achieved.
  • Keywords
    Global Positioning System; Kalman filters; accelerometers; autonomous aerial vehicles; barometers; calibration; inertial navigation; inertial systems; nonlinear filters; position measurement; rotors (mechanical); sensor fusion; state estimation; EKF; GPS; IMU; accelerometer measurement; autonomous flight; autonomous quadrotor; barometer; calibration; degrees of freedom; extended Kalman filter; inertial measurement unit; inertial position estimation; mathematical model; parameter determination; sensor data fusion; state variable estimation; systematic bias; Accelerometers; Equations; Global Positioning System; Kalman filters; Mathematical model; State estimation;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Instrumentation and Measurement Technology Conference (I2MTC) Proceedings, 2014 IEEE International
  • Conference_Location
    Montevideo
  • Type

    conf

  • DOI
    10.1109/I2MTC.2014.6860982
  • Filename
    6860982