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

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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.

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Notes

  1. \(m_{rj, i}\) denotes the \((r+j)\)th order moment associated to the ith section.

  2. http://www.ros.org.

  3. http://www.asctec.de.

  4. GSL - GNU Scientific Library: http://www.gnu.org/software/gsl/.

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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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Authors and Affiliations

  1. PRISMA Lab, Dipartimento di Ingegneria Elettrica e Tecnologie dell’Informazione, Università degli Studi di Napoli Federico II, Via Claudio 21, 80125, Naples, Italy

    Rafik Mebarki, Vincenzo Lippiello & Bruno Siciliano

Authors
  1. Rafik Mebarki
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  2. Vincenzo Lippiello
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  3. Bruno Siciliano
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Corresponding author

Correspondence to Rafik Mebarki.

Additional information

This paper is an extended version of (Mebarki and Lippiello 2014) that received the Best Paper Award of the 12th IEEE International Symposium on Safety, Security, and Rescue Robotics held in Hokkaido, Japan.

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Mebarki, R., Lippiello, V. & Siciliano, B. Vision-based and IMU-aided scale factor-free linear velocity estimator. Auton Robot 41, 903–917 (2017). https://doi.org/10.1007/s10514-016-9561-5

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