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Sensor-Fusion-Based Trajectory Reconstruction for Quadrotor Drones

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Computer Vision, Imaging and Computer Graphics Theory and Applications (VISIGRAPP 2018)

Part of the book series: Communications in Computer and Information Science ((CCIS,volume 997))

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Abstract

In this paper, we propose a novel sensor-fusion-based method to eliminate errors of MEMS IMUs, and reconstruct trajectory of quadrotor drones. MEMS IMUs are widely equipped in quadrotor drones and other mobile devices. Unfortunately, they carry a lot of inherent errors, which cause poor results in trajectory reconstruction. To solve this problem, an error model for accelormeter signals in MEMS IMUs is established. In this model, the error is composed of a bias component and a noise component. First, a low-pass filter with downsampling is applied to reduce the noise component. Then, the bias component is detected and eliminated dynamically with the assistance of other sensors. Finally, the trajectory of the drone is reconstructed through integration of the calibrated accelormeter data. We apply our trajectory reconstruction method on Parrot AR.Drone 2.0 which employs a low-cost MEMS IMU. The experimental results prove its effectiveness. This method can theoretically be applied to any other mobile devices which are equipped with MEMS IMUs.

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Notes

  1. 1.

    http://developer.parrot.com/products.html.

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Acknowledgements

This work is partially supported by National Key Research and Development Program of China (2016QY02D0304) and NSFC grants (61602012).

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Authors and Affiliations

  1. Institute of Computer Science and Technology, Peking University, Beijing, China

    Jielei Zhang, Jie Feng & Bingfeng Zhou

Authors
  1. Jielei Zhang
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  2. Jie Feng
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  3. Bingfeng Zhou
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Corresponding author

Correspondence to Jielei Zhang .

Editor information

Editors and Affiliations

  1. University of Strasbourg, Strasbourg, France

    Dominique Bechmann

  2. University of Genoa, Genoa, Italy

    Manuela Chessa

  3. University of Lisbon, Lisbon, Portugal

    Ana Paula Cláudio

  4. Research Innovation Center, Apple Inc., San Jose, CA, USA

    Francisco Imai

  5. Linnaeus University, Växjö, Kronobergs Län, Sweden

    Andreas Kerren

  6. LISA - ISTIA, University of Angers, Angers, France

    Paul Richard

  7. University of Groningen, Groningen, The Netherlands

    Alexandru Telea

  8. Jean Monnet University, Saint-Etienne, France

    Alain Tremeau

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Zhang, J., Feng, J., Zhou, B. (2019). Sensor-Fusion-Based Trajectory Reconstruction for Quadrotor Drones. In: Bechmann, D., et al. Computer Vision, Imaging and Computer Graphics Theory and Applications. VISIGRAPP 2018. Communications in Computer and Information Science, vol 997. Springer, Cham. https://doi.org/10.1007/978-3-030-26756-8_1

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  • DOI: https://doi.org/10.1007/978-3-030-26756-8_1

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  • Publisher Name: Springer, Cham

  • Print ISBN: 978-3-030-26755-1

  • Online ISBN: 978-3-030-26756-8

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