Skip to main content
SpringerLink
Log in
Book cover

Experimental Robotics pp 273–288Cite as

State Estimation for Indoor and Outdoor Operation with a Micro-Aerial Vehicle

  • Chapter

Part of the book series: Springer Tracts in Advanced Robotics ((STAR,volume 88))

Abstract

In this work, we detail a methodology for estimating the state of a microaerial vehicle (MAV) as it transitions between different operating environments with varying applicable sensors. We ensure that the estimate is smooth and continuous throughout and provide an associated quality measure of the state estimate. We address the challenge of maintaining consistency between local and global measurements and propose a strategy to recursively estimate the transform between different coordinate frames. We close with experiments that validate the approach and the resulting performance as a MAV navigates between mixed indoor and outdoor environments.

This is a preview of subscription content, log in via an institution.

Chapter
USD   29.95
Price excludes VAT (USA)
  • Available as PDF
  • Read on any device
  • Instant download
  • Own it forever
eBook
USD   169.00
Price excludes VAT (USA)
  • Available as PDF
  • Read on any device
  • Instant download
  • Own it forever
Softcover Book
USD   219.99
Price excludes VAT (USA)
  • Compact, lightweight edition
  • Dispatched in 3 to 5 business days
  • Free shipping worldwide - see info
Hardcover Book
USD   219.99
Price excludes VAT (USA)
  • Durable hardcover edition
  • Dispatched in 3 to 5 business days
  • Free shipping worldwide - see info

Tax calculation will be finalised at checkout

Purchases are for personal use only

Learn about institutional subscriptions

Preview

Unable to display preview. Download preview PDF.

Unable to display preview. Download preview PDF.

References

  1. Shen, S., Michael, N., Kumar, V.: Autonomous multi-floor indoor navigation with a computationally constrained MAV. In: Proc. of the IEEE Intl. Conf. on Robot. and Autom., Shanghai, China, pp. 20–25 (May 2011)

    Google Scholar 

  2. Julier, S.J., Uhlmann, J.K.: A new extension of the kalman filter to nonlinear systems. In: Kadar, I. (ed.) Proc. of SPIE, vol. 3068, pp. 182–193 (July 1997)

    Google Scholar 

  3. Merwe, R.V.D., Wan, E.A., Julier, S.I.: Sigma-point kalman filters for nonlinear estimation: Applications to integrated navigation. In: Proc. of AIAA Guidance, Navigation, and Controls Conf., Providence, RI (August 2004)

    Google Scholar 

  4. Grzonka, S., Grisetti, G., Burgard, W.: Towards a navigation system for autonomous indoor flying. In: Proc. of the IEEE Intl. Conf. on Robot. and Autom., Kobe, Japan, pp. 2878–2883 (May 2009)

    Google Scholar 

  5. Bachrach, A.G.: Autonomous flight in unstructured and unknown indoor environments. Master’s thesis, MIT, Cambridge, MA (September 2009)

    Google Scholar 

  6. Blösch, M., Weiss, S., Scaramuzza, D., Siegwart, R.: Vision based MAV navigation in unknown and unstructured environments. In: Proc. of the IEEE Intl. Conf. on Robot. and Autom., Anchorage, AK, pp. 21–28 (May 2010)

    Google Scholar 

  7. Carlson, J.: Mapping large urban environments with GPS-aided SLAM. Ph.D. dissertation, CMU, Pittsburgh, PA (July 2010)

    Google Scholar 

  8. Schleicher, D., Bergasa, L.M., Ocaña, M., Barea, R., López, E.: Real-time hierarchical GPS aided visual SLAM on urban environments. In: Proc. of the IEEE Intl. Conf. on Robot. and Autom., Kobe, Japan, pp. 4381–4386 (May 2009)

    Google Scholar 

  9. Moore, D.C., Huang, A.S., Walter, M., Olson, E.: Simultaneous local and global state estimation for robotic navigation. In: Proc. of the IEEE Intl. Conf. on Robot. and Autom., Kobe, Japan, pp. 3794–3799 (May 2009)

    Google Scholar 

  10. Weinmann, A.: Uncertain Models and Robust Control. Springer, New York (1991)

    Book  Google Scholar 

  11. Bosse, M., Newman, P., Leonard, J., Soika, M., Feiten, W., Teller, S.: An atlas framework for scalable mapping. In: Proc. of the IEEE Intl. Conf. on Robot. and Autom., Taipei, Taiwan, vol. 2, pp. 1899–1906 (September 2003)

    Google Scholar 

  12. Estrada, C., Neira, J., Tardos, J.D.: Hierarchical SLAM: Real-time accurate mapping of large environments. IEEE Trans. Robot. 21(4), 588–596 (2005)

    Article  Google Scholar 

  13. Dellaert, F., Kaess, M.: Square root SAM: Simultaneous localization and mapping via square root information smoothing. Intl. J. Robot. Research 25(12), 1181–1203 (2006)

    Article  MATH  Google Scholar 

  14. Kaess, M., Ranganathan, A., Dellaert, F.: iSAM: Incremental smoothing and mapping. IEEE Trans. Robot. 24(6), 1365–1378 (2008)

    Article  Google Scholar 

  15. Censi, A.: On achievable accuracy for pose tracking. In: Proc. of the IEEE Intl. Conf. on Robot. and Autom., Kobe, Japan, pp. 1–7 (May 2009)

    Google Scholar 

  16. Smith, R., Self, M., Cheeseman, P.: Estimating uncertain spatial relationships in robotics. In: Proc. of the IEEE Intl. Conf. on Robot. and Autom., Rayleigh, NC, vol. 4, p. 850 (March 1987)

    Google Scholar 

  17. Dryanovski, I., Morris, W., Jizhong, X.: Multi-volume occupancy grids: An efficient probabilistic 3d mapping model for micro aerial vehicles. In: Proc. of the IEEE/RSJ Intl. Conf. on Intell. Robots and Syst., Taipei, Taiwan, pp. 1553–1559 (October 2010)

    Google Scholar 

  18. Olson, E.: Real-time correlative scan matching. In: Proc. of the IEEE Intl. Conf. on Robot. and Autom., Kobe, Japan, pp. 4387–4393 (May 2009)

    Google Scholar 

  19. Ascending Technologies, GmbH (February 2012), http://www.asctec.de/

  20. Robot Operating System (February 2012), http://www.ros.org/

Download references

Author information

Authors and Affiliations

  1. GRASP Laboratory, University of Pennsylvania, Philadelphia, PA, 19104, USA

    Shaojie Shen & Nathan Michael

Authors
  1. Shaojie Shen
    View author publications

    You can also search for this author in PubMed Google Scholar

  2. Nathan Michael
    View author publications

    You can also search for this author in PubMed Google Scholar

Corresponding author

Correspondence to Shaojie Shen .

Editor information

Editors and Affiliations

  1. (RAMS) Institute for Systems Research, Maryland Robotics Center, University of Maryland, Room 0160, Bldg 088, Glenn L. Martin Hall, College Park, 20742, Maryland, USA

    Jaydev P. Desai

  2. , Centre for Intelligent Machines, McGill University, Room 419, 3480 University Street, Montreal, H3A 2A7, Québec, Canada

    Gregory Dudek

  3. , Department of Computer Science, Stanford University, Stanford, 94305-9010, California, USA

    Oussama Khatib

  4. , School of Engineering & Applied Science, University of Pennsylvania, 107 Towne Building, 220 South 33rd Street, Philadelphia, 19104-6391, Pennsylvania, USA

    Vijay Kumar

Rights and permissions

Reprints and permissions

Copyright information

© 2013 Springer International Publishing Switzerland

About this chapter

Cite this chapter

Shen, S., Michael, N. (2013). State Estimation for Indoor and Outdoor Operation with a Micro-Aerial Vehicle. In: Desai, J., Dudek, G., Khatib, O., Kumar, V. (eds) Experimental Robotics. Springer Tracts in Advanced Robotics, vol 88. Springer, Heidelberg. https://doi.org/10.1007/978-3-319-00065-7_20

Download citation

  • DOI: https://doi.org/10.1007/978-3-319-00065-7_20

  • Publisher Name: Springer, Heidelberg

  • Print ISBN: 978-3-319-00064-0

  • Online ISBN: 978-3-319-00065-7

  • eBook Packages: EngineeringEngineering (R0)

Publish with us

Policies and ethics

Search

Navigation