Fast Relative Pose Calibration for Visual and Inertial Sensors

  • Jonathan Kelly
  • Gaurav S. Sukhatme
Part of the Springer Tracts in Advanced Robotics book series (STAR, volume 54)


Accurate vision-aided inertial navigation depends on proper calibration of the relative pose of the camera and the inertial measurement unit (IMU). Calibration errors introduce bias in the overall motion estimate, degrading navigation performance - sometimes dramatically. However, existing camera-IMU calibration techniques are difficult, time-consuming and often require additional complex apparatus. In this paper, we formulate the camera-IMU relative pose calibration problem in a filtering framework, and propose a calibration algorithm which requires only a planar camera calibration target. The algorithm uses an unscented Kalman filter to estimate the pose of the IMU in a global reference frame and the 6-DoF transform between the camera and the IMU. Results from simulations and experiments with a low-cost solid-state IMU demonstrate the accuracy of the approach.


Inertial Measurement Unit Inertial Sensor Calibration Target Calibration Algorithm Sigma Point 
These keywords were added by machine and not by the authors. This process is experimental and the keywords may be updated as the learning algorithm improves.


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Copyright information

© Springer-Verlag Berlin Heidelberg 2009

Authors and Affiliations

  • Jonathan Kelly
    • 1
  • Gaurav S. Sukhatme
    • 1
  1. 1.Department of Computer ScienceUniversity of Southern California 

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