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Accurate Image Depth Determination for Autonomous Vehicle Navigation

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Aerospace Robotics III

Part of the book series: GeoPlanet: Earth and Planetary Sciences ((GEPS))

Abstract

This paper examines accurate image depth determination to achieve accurate navigation. Accurate navigation is critical for Unmanned Aerial Vehicle or UAV aerial refueling and, also, space debris clearance operations. At this point it is not the intention to generate a definitive depth performance study, rather the intention is to gain an understanding of the kind of depth performance which might be possible for a small UAV or space-based robot flying close in and far away, at depths of 2 and 20 m, for example. The theory behind image depth calculation is explained and then synthetic pixel data are manufactured to determine a 95% confidence interval on image depth under various errors conditions. It is shown that without image rectification and no knowledge of camera rotation, accurate depth can only be calculated for stereo cameras pointing without any axial rotations. With image rectification and under the stated conditions, image depth can be calculated with 8.2% or less absolute relative error. Future research is discussed.

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Abbreviations

CI:

Confidence Interval

GPS:

Global Positioning System

INU:

Inertial Navigation Unit

MAV:

Mini- or micro-UAV

SVD:

Singular Value Decomposition

UAV:

Unmanned Aerial Vehicle

References

  • Bachrach A, Prentice S, He R, Henry P, Huang A, Krainin M, Maturana D, Fox D, Roy N (2012) Estimation, planning and mapping for autonomous flight using an RGB-D camera in GPS-denied environments. Int J Robot Res 31(11):1320–1343. https://doi.org/10.1177/0278364912455256

    Article  Google Scholar 

  • Bouguet J (2015) Camera calibration toolbox for matlab. http://www.vision.caltech.edu/bouguetj/calib_doc. Accessed 18 Dec 2009

  • Fraundorfer F, Scaramuzza D (2012) Visual odometry part II: matching, robustness, optimization, and applications. IEEE Robot Autom Mag 19(2):78–90

    Article  Google Scholar 

  • Fravolini M, Campa G, Ficola A, Napolitano M, Seanor B (2006) Modeling and control issues for machine vision-based autonomous aerial refueling for UAVs. J Guid Control Dyn (unpublished)

    Google Scholar 

  • Hartley R, Zisserman A (2003) Multiple view geometry in computer vision. Cambridge University Press, Cambridge

    MATH  Google Scholar 

  • Heikkila J (2000) Geometric camera calibration using circular control points. IEEE Trans Pattern Anal Mach Intell 22(10):1066–1077

    Article  Google Scholar 

  • Hu G, MacKunis W, Gans N, Dixon W, Chen J, Behal A, Dawson D (2009) Homography-based visual servo control with imperfect camera calibration. IEEE Trans Autom Control 54(6):1318–1324

    Article  MathSciNet  Google Scholar 

  • Iocchi L (unavailable) Stereo vision: triangulation. http://www.dis.uniroma1.it/~iocchi/stereo/triang.html. Accessed 27 Jan 2011

  • Jaehne B (2001) 3-D imaging. In: Jaehne B (ed) Digital image processing, 5th edn. Springer, Berlin

    Google Scholar 

  • Kaiser K, Gans N, Mehta S, Dixon W (2006) Position and orientation of an aerial vehicle through chained, vision-based pose reconstruction. In: Proceedings of the AIAA guidance, navigation, and control conference and exhibit. AIAA-02006-6719

    Google Scholar 

  • Kaiser K, Gans N, Dixon W (2007) Localization and control of an aerial vehicle through chained, vision-based pose reconstruction. In: IEEE proceedings of the 2007 American control conference, pp 5934–5939

    Google Scholar 

  • Kanade T, Amidi O, Ke Q (2004) Real-time and 3D vision for autonomous small and micro air vehicles. In: Proceedings of the 43rd IEEE conference on decision and control, pp 1655–1662

    Google Scholar 

  • Loop C, Zhang Z (1999) Computing rectifying homographies for stereo vision. Proc IEEE Conf Comput Vis Pattern Recognit 1:125–131

    Google Scholar 

  • Mendenhall W (1968) Introduction to linear models and the design and analysis of experiments. Wadsworth Publishing Company, Belmont, California

    Google Scholar 

  • Michaelson E, Kirchhof M, Stilla U (2004) Sensor pose inference from airborne videos by decomposing homography estimates. In: Proceedings of the XXth ISPRS congress, Technical Commission III

    Google Scholar 

  • Nister D, Naroditsky O, Bergen J (2006) Visual odometry for ground vehicle applications. J Field Robot 23(1):3–20

    Article  Google Scholar 

  • Sasiadek J, Walker M (2008) Vision-based UAV navigation. In: Proceedings of the AIAA guidance, navigation, and control conference and exhibit. AIAA 2008-6667

    Google Scholar 

  • Sasiadek J, Walker M (2010) Feature detector performance for UAV navigation. In: Proceedings of IASTED modelling, identification, and control conference. https://doi.org/10.2316/p.2010.675-114

  • Sasiadek J, Walker M, Krzyzak A (2010) Feature matching for UAV navigation in urban environments. In: Proceedings of conference methods and models in automation and robotics. https://doi.org/10.1109/mmar.2010.5587244

  • Sasiadek J, Walker M, Krzyzak A (2011) Accurate feature matching for autonomous vehicle navigation in urban environments. In: Proceedings of conference methods and models in automation and robotics. https://doi.org/10.1109/mmar.2011.6031318

  • Slonka M, Hlavac V, Boyle R (2008) Image processing, analysis, and machine vision. Thomson, USA

    Google Scholar 

  • Strat T (1984) Recovering the camera parameters from a transformation matrix. In: Proceedings of DARPA image understanding workshop, pp 264–271

    Google Scholar 

  • Torr P, Zisserman A (2000) Feature based methods for structure and motion estimation. In: Vision algorithms: theory and practice: international workshop on vision algorithms, pp 278–294

    Chapter  Google Scholar 

  • Tsai R (1987) A versatile camera calibration technique for high-accuracy 3D machine vision metrology using off-the-shelf TV cameras and lenses. IEEE J Robot Autom RA-3(4):323–344

    Article  Google Scholar 

  • Valasek J, Gunnam K, Kimmet J, Tandale M, Junkins J, Hughes D (2005) Vision based sensor and navigation system for autonomous air refueling. J Guid Control Dyn 28(5):979–989

    Article  Google Scholar 

  • Volpe JA (2001) N.T.S. Center, Vulnerability assessment of the transport infrastructure relying on the global positioning system. Report, Office of the Assistant Secretary for Transportation Policy, U.S. Department of Transportation

    Google Scholar 

  • Walker M, Sasiadek J (2013) Accurate pose determination for autonomous vehicle navigation. In: Proceedings of conference methods and models in automation and robotics. https://doi.org/10.1109/mmar.2013.6669933

  • Webb T, Prazenica R, Kurdial A, Lind R (2007) Vision-based state estimation for autonomous micro air vehicles. J Guid Control Dyn 30(3):816–826

    Article  Google Scholar 

  • Zhang Z (2000) A flexible new technique for camera calibration. IEEE Trans Pattern Anal Mach Intell 22(11):1330–1334

    Article  Google Scholar 

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Authors and Affiliations

  1. Department of Mechanical and Aerospace Engineering, Carleton University, Ottawa, ON, Canada

    Jurek Z. Sasiadek & Mark J. Walker

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  1. Jurek Z. Sasiadek
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  2. Mark J. Walker
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Correspondence to Mark J. Walker .

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Editors and Affiliations

  1. Mechanical and Aerospace Engineering, Carleton University, Ottawa, ON, Canada

    Jerzy Sasiadek

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Sasiadek, J.Z., Walker, M.J. (2019). Accurate Image Depth Determination for Autonomous Vehicle Navigation. In: Sasiadek, J. (eds) Aerospace Robotics III. GeoPlanet: Earth and Planetary Sciences. Springer, Cham. https://doi.org/10.1007/978-3-319-94517-0_5

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