Inertial Yaw-Independent Velocity and Attitude Estimation for High-Speed Quadrotor Flight

James Svacha, Giuseppe Loianno, Vijay Kumar

Research output: Contribution to journalArticle

Abstract

This letter addresses the velocity and attitude estimation of a quadrotor using motor speeds and inertial measurement unit (IMU) data. This result is obtained through a novel filter that employs a first-order drag model, which allows the velocity to be observed through the drag forces acting on the quadrotor. These forces are measured with the IMU. Compared to our previous contribution [J. Svacha, K. Mohta, M. Watterson, G. Loianno, and V. Kumar, 'Inertial velocity and attitude estimation for quadrotors,' in Proc. IEEE/RSJ Int. Conf. Intell. Robots Syst., Oct. 2018, pp. 1-9.], decoupling the attitude into a yaw-tilt convention results in the tilt and velocity in the body-fixed frame being independent of the yaw. Thus, the velocity and attitude estimates are no longer affected by yaw drifts obtained from dead-reckoning procedures. The camera available on the vehicle can optionally be employed to recover the yaw in a computationally efficient way without requiring RANSAC, instead using the estimated velocity and attitude from the filter. The IMU is concurrently used to estimate the thrust, linear drag coefficients, and accelerometer biases. Experimental results on a quadrotor platform show the feasibility of the proposed approach.

Original languageEnglish (US)
Article number8620279
Pages (from-to)1109-1116
Number of pages8
JournalIEEE Robotics and Automation Letters
Volume4
Issue number2
DOIs
StatePublished - Apr 2019

Keywords

  • Aerial systems: perception and autonomy
  • sensor fusion

ASJC Scopus subject areas

  • Control and Systems Engineering
  • Biomedical Engineering
  • Human-Computer Interaction
  • Mechanical Engineering
  • Computer Vision and Pattern Recognition
  • Computer Science Applications
  • Control and Optimization
  • Artificial Intelligence

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