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Autonomous Robots

, Volume 41, Issue 4, pp 903–917 | Cite as

Vision-based and IMU-aided scale factor-free linear velocity estimator

  • Rafik Mebarki
  • Vincenzo Lippiello
  • Bruno Siciliano
Article

Abstract

This paper presents a new linear velocity estimator based on the unscented Kalman filter and making use of image information aided with inertial measurements. The proposed technique is independent of the scale factor in case of planar observed scene and does not require a priori knowledge of the scene. Image moments of virtual objects, i.e. sets of classical image features such as corners collected online, are employed as the sole correcting information to be fed back to the estimator. Experimental results performed with a quadrotor equipped with a fisheye camera highlight the potential of the proposed approach.

Keywords

UAV quadrotors Velocity estimation Computer vision Data fusion Kalman filter 

Notes

Acknowledgments

The research leading to these results has been supported by the ARCAS and SHERPA collaborative projects, which have received funding from the European Community’s Seventh Framework Programme (FP7/2007-2013) under grant agreements ICT-287617 and ICT-600958, respectively. The authors are solely responsible for its content. It does not represent the opinion of the European Community and the Community is not responsible for any use that might be made of the information contained therein.

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Copyright information

© Springer Science+Business Media New York 2016

Authors and Affiliations

  • Rafik Mebarki
    • 1
  • Vincenzo Lippiello
    • 1
  • Bruno Siciliano
    • 1
  1. 1.PRISMA Lab, Dipartimento di Ingegneria Elettrica e Tecnologie dell’InformazioneUniversità degli Studi di Napoli Federico IINaplesItaly

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