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Fast Moving UAV Collision Avoidance Using Optical Flow and Stereovision

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Part of the book series: Lecture Notes in Computer Science ((LNAI,volume 10192))

Abstract

Unmanned aerial vehicles are becoming popular, but their autonomous operation is constrained by their collision avoidance ability in high-velocity movement. We propose a simple collision avoidance scheme for fast, business-grade fixed-wing aircraft which is based on optical flow and stereovision. We calculate optical flow on parts of the image that are essential for collision avoidance and enlarge the analysed area only as long, as the framerate allows, thus avoiding the need to stretch calculations over several frames.

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References

  1. Menze, M., Geiger, A.: Object scene flow for autonomous vehicles. In: Conference on Computer Vision and Pattern Recognition (CVPR) (2015)

    Google Scholar 

  2. Menze, M., Heipke, C., Geiger, A.: Joint 3D estimation of vehicles and scene flow. In: ISPRS Workshop on Image Sequence Analysis (ISA) (2015)

    Google Scholar 

  3. Sizintsev, M., Kuthirummal, S., Samarasekera, S., Kumar, R., Sawhney, H.S., Chaudhry, A.: GPU accelerated realtime stereo for augmented reality. In: 3DPVT (2010)

    Google Scholar 

  4. Derome, M., Plyer, A., Sanfourche, M., Besnerais, G.: A prediction-correction approach for real-time optical flow computation using stereo. In: Rosenhahn, B., Andres, B. (eds.) GCPR 2016. LNCS, vol. 9796, pp. 365–376. Springer, Heidelberg (2016). doi:10.1007/978-3-319-45886-1_30

    Chapter  Google Scholar 

  5. Baker, S., Matthews, I.: Lucas-Kanade 20 years on: a unifying framework. IJCV 56(3), 221–255 (2004)

    Article  Google Scholar 

  6. Bouguet, J.-Y.: Pyramidal implementation of the Lucas Kanade feature tracker. Intel Corporation, Microprocessor Research Labs (2000)

    Google Scholar 

  7. Sanfourche, M., Vittori, V., Le Besnerais, G.: eVO: a realtime embedded stereo odometry for MAV applications. In: IROS (2013)

    Google Scholar 

  8. Le Besnerais, G., Champagnat, F.: Dense optical flow by iterative local window registration. In: ICIP (2005)

    Google Scholar 

  9. Plyer, A., Le Besnerais, G., Champagnat, F.: Folki-GPU: a powerful and versatile cuda code for real-time optical flow computation. In: GPU Technology Conference (2009)

    Google Scholar 

  10. Plyer, A., Le Besnerais, G., Champagnat, F.: Massively parallel Lucas Kanade optical flow for real-time video processing applications. J. Real-Time Image Proc. 11(4), 713–730 (2016)

    Article  Google Scholar 

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Acknowledgements

This work has been supported by the National Centre for Research and Development, Poland in the frame of project POIR.01.02.00-00-0009/2015 “System of autonomous landing of an UAV in unknown terrain conditions on the basis of visual data”.

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Correspondence to Damian Pęszor .

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Pęszor, D., Wojciechowska, M., Wojciechowski, K., Szender, M. (2017). Fast Moving UAV Collision Avoidance Using Optical Flow and Stereovision. In: Nguyen, N., Tojo, S., Nguyen, L., Trawiński, B. (eds) Intelligent Information and Database Systems. ACIIDS 2017. Lecture Notes in Computer Science(), vol 10192. Springer, Cham. https://doi.org/10.1007/978-3-319-54430-4_55

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  • DOI: https://doi.org/10.1007/978-3-319-54430-4_55

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  • Publisher Name: Springer, Cham

  • Print ISBN: 978-3-319-54429-8

  • Online ISBN: 978-3-319-54430-4

  • eBook Packages: Computer ScienceComputer Science (R0)

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