• DocumentCode
    3586977
  • Title

    A denoising and drift-control approach for UAV trajectory tracking

  • Author

    Chaoqun Wang ; Wei Liu ; Meng, Max Q.-H

  • Author_Institution
    Dept. of Electron. Eng., Chinese Univ. of HongKong, Hong Kong, China
  • fYear
    2014
  • Firstpage
    1714
  • Lastpage
    1718
  • Abstract
    As part of dead reckoning, inertial navigation has been developed for many years in locating the vehicle without GPS. We employ the technology on a quadrotor platform to track the trajectory of the vehicle. In this paper, a new method was designed to make the tracking result more precisely. To achieve this, we firstly smooth the sensor data by minus offset dynamically and adopt Kalman Filtering algorithm. Then we detect velocity and correct the wrong value in time to decrease drift in displacement. This is an important step in locating the vehicle simply by odometry.
  • Keywords
    Kalman filters; aircraft control; autonomous aerial vehicles; helicopters; inertial navigation; trajectory control; velocity control; Kalman filtering algorithm; UAV; dead reckoning; denoising approach; drift-control approach; inertial navigation; odometry; quadrotor platform; trajectory tracking; velocity control; Acceleration; Brushless motors; Kalman filters; Robot sensing systems; Trajectory; Vehicles;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Robotics and Biomimetics (ROBIO), 2014 IEEE International Conference on
  • Type

    conf

  • DOI
    10.1109/ROBIO.2014.7090582
  • Filename
    7090582