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Image-Directed Sampling for Geometric Modeling of Lunar Terrain

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Field and Service Robotics

Part of the book series: Springer Tracts in Advanced Robotics ((STAR,volume 92))

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Abstract

Geometric modeling from range scanners can be vastly improved by sampling the scene with a Nyquist criterion. This work presents a method to estimate frequency content a priori from intensity imagery using wavelet analysis and to utilize these estimates in efficient single-view sampling. The key idea is that under certain constrained and estimable image formation conditions, images are a strong predictor of surface frequency. This approach is explored in the context of lunar application to enhance robotic modeling. Experimentation on simulated data and in artificial lunar terrain at aerial and ground rover scales is documented. Results show up to 40 % improvement in MSE reconstruction error. Lastly, a class of image-directed range sensors is described and a hardware implementation of this paradigm on a structured light scanner is demonstrated.

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Acknowledgments

The authors acknowledge Kevin Peterson, Heather Jones and Jason Koenig for use of lunar model data.

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Authors and Affiliations

  1. Robotics Institute, Carnegie Mellon University, Pittsburgh, USA

    Uland Wong, Warren Whittaker & Red Whittaker

  2. The Engine Company, LLC, Baltimore, USA

    Ben Garney

Authors
  1. Uland Wong
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  2. Ben Garney
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  3. Warren Whittaker
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  4. Red Whittaker
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Corresponding author

Correspondence to Uland Wong .

Editor information

Editors and Affiliations

  1. Department of Aerospace Engineering, Tohoku University, Sendai, Japan

    Kazuya Yoshida

  2. Tohoku University Graduate School of Information Sciences, Sendai, Japan

    Satoshi Tadokoro

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© 2014 Springer-Verlag Berlin Heidelberg

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Wong, U., Garney, B., Whittaker, W., Whittaker, R. (2014). Image-Directed Sampling for Geometric Modeling of Lunar Terrain. In: Yoshida, K., Tadokoro, S. (eds) Field and Service Robotics. Springer Tracts in Advanced Robotics, vol 92. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-40686-7_31

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  • DOI: https://doi.org/10.1007/978-3-642-40686-7_31

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  • Publisher Name: Springer, Berlin, Heidelberg

  • Print ISBN: 978-3-642-40685-0

  • Online ISBN: 978-3-642-40686-7

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