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Recreation of 3D Models of Objects Using MAV and Skanect

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Part of the book series: Advances in Intelligent Systems and Computing ((AISC,volume 1108))

Abstract

Mapping of static objects in an indoor environment is a process to obtain the description of that environment. Simultaneous localization and mapping (SLAM) is an active area of research in mobile robotics and localization technology. To accomplish enhanced performance with low cost sensors, Microsoft Kinect has been mounted on a developed aerial platform in association with Skanect. Skanect transforms the structure sensor Kinect into a less expensive 3D scanner that can create 3D meshes. An experimental result shows how the proposed approach is able to produce reliable 3D reconstruction from the Kinect data.

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References

  1. Zhou, W., Jaime, V., Dissanayake, G.: Information efficient 3D visual SLAM for unstructured domains. IEEE Trans. Robot. Autom. 24, 1078–1087 (2008)

    Article  Google Scholar 

  2. Kinect for Windows: (n.d.). Microsoft Developer Network. http://msdn.microsoft.com/en-us/library/jj131033.aspx

  3. DragonFly: (n.d.). DragonFly X4. http://www.draganfly.com/uav-helicopter/draganflyer-x4/specifications/. Accessed Sept 2013

  4. Beard, R.: Quadrotor dynamics and control rev 0.1. (2008)

    Google Scholar 

  5. “gumstix: finally! - a very small linux machine”. gumstix.org. 8 April 2004. Archived from the original on 8 April 2004. http://web.archive.org/web/20040408235922, http://www.gumstix.org/index.html. Accessed 29 July 2009

  6. https://skanect.occipital.com/

  7. Fischler, M.A., Bolles, R.C.: Random sample consensus: a paradigm for model fitting with applications to image analysis and automated cartography. Commun. ACM 24(6), 381–395 (1981)

    Article  MathSciNet  Google Scholar 

  8. Genevois, T., Zielinska, T.: A simple and efficient implementation of EKF-based SLAM relying on laser scanner in complex indoor environment. J. Autom. Mob. Robot. Intell. Syst. 8, 58–67 (2014). https://doi.org/10.14313/JAMRIS_2-2014/20

    Article  Google Scholar 

  9. Endres, F., Hess, J., Engelhard, N., Sturm, J., Cremers, D., Burgard, W.: An evaluation of the RGB-D SLAM system. In: Proceedings of the IEEE International Conference on Robotics and Automation (ICRA) (2012)

    Google Scholar 

  10. Srividhya, S., Prakash, S.: Performance evaluation of various feature detection algorithms in VSLAM. PARIPEX Indian J. Res. 6(2), 386–388 (2017)

    Google Scholar 

  11. Bay, H., Tuytelaars, T., Van Gool, L.: SURF: speeded up robust features. In: European Conference on Computer Vision. Springer, Heidelberg (2006)

    Google Scholar 

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Correspondence to S. Srividhya .

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✓ No humans/animals involved in this research work.

✓ We have used our own data.

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Srividhya, S., Prakash, S., Elangovan, K. (2020). Recreation of 3D Models of Objects Using MAV and Skanect. In: Smys, S., Tavares, J., Balas, V., Iliyasu, A. (eds) Computational Vision and Bio-Inspired Computing. ICCVBIC 2019. Advances in Intelligent Systems and Computing, vol 1108. Springer, Cham. https://doi.org/10.1007/978-3-030-37218-7_29

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