Skip to main content

Pose-Sequence-Based Graph Optimization Using Indoor Magnetic Field Measurements

  • Conference paper
Robot Intelligence Technology and Applications 3

Part of the book series: Advances in Intelligent Systems and Computing ((AISC,volume 345))

  • 3941 Accesses

Abstract

In this paper we provide a method of handling loop closings in a simultaneous localization and mapping (SLAM) problem by employing indoor magnetic measurements and pose graph optimization. Since the magnetic field in indoor environments has unique spatial features, we can exploit these characteristics to generate the constraints for the pose graph-based SLAM. Specifically, whenever certain motion conditions are satisfied, a series of robot poses along with their magnetic measurements can be grouped into a sequence. A loop closing algorithm is then proposed based on the sequence and applied to the pose graph optimization. Experimental results show that the proposed SLAM system with only wheel encoders and a single magnetometer obtains comparable results with a reference-level SLAM system in terms of robot trajectory, by correctly detecting the loop closings.

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

Access this chapter

Subscribe and save

Springer+ Basic
$34.99 /Month
  • Get 10 units per month
  • Download Article/Chapter or eBook
  • 1 Unit = 1 Article or 1 Chapter
  • Cancel anytime
Subscribe now

Buy Now

Chapter
USD 29.95
Price excludes VAT (USA)
  • Available as PDF
  • Read on any device
  • Instant download
  • Own it forever

Tax calculation will be finalised at checkout

Purchases are for personal use only

Institutional subscriptions

Preview

Unable to display preview. Download preview PDF.

Unable to display preview. Download preview PDF.

Similar content being viewed by others

References

  1. Thrun, S., Burgard, W., Fox, D.: Probabilistic Robotics. The MIT Press, Cambridge (2005)

    MATH  Google Scholar 

  2. Fernandez-Madrigeal, J., Claraco, J.L.: Simultaneous Localization and Mapping for Mobile Robots: Introduction and Methods. Information Science Reference, Hershey (2013)

    Book  Google Scholar 

  3. Kuemmerle, R., Grisetti, G., Strasdat, H., Konolige, K., Burgard, W.: g2o: A general framework for graph optimization. In: Proc. IEEE International Conference on Robotics and Automation (ICRA2011), Shanghai, China, pp. 3607–3613 (May 2011)

    Google Scholar 

  4. Kaess, M., Johannsson, H., Roberts, R., Ila, V., Leonard, J., Dellaert, F.: iSAM2: Incremental smoothing and mapping using the Bayes tree. The International Journal of Robotics Research 31, 217–236 (2012)

    Article  Google Scholar 

  5. Lee, D., Myung, H.: Solution to the SLAM problem in low dynamic environments using a pose graph and an RGB-D sensor. Sensors 14(7), 12467–12496 (2014)

    Article  Google Scholar 

  6. Afzal, M., Renaudin, V., Lachapelle, G.: Magnetic field based heading estimation for pedestrian navigation environments. In: Proc. IEEE International Conference on Indoor Positioning and Indoor Navigation (IPIN2011), Guimaraes, Portugal, pp. 1–10 (September 2011)

    Google Scholar 

  7. Bird, J., Arden, D.: Indoor navigation with foot-mounted strapdown inertial navigation and magnetic sensors [emerging opportunities for localization and tracking]. IEEE Wireless Commun. Mag. 18(2), 28–35 (2011)

    Article  Google Scholar 

  8. Haverinen, J., Kemppainen, A.: A geomagnetic field based positioning technique for underground mines. In: Proc. IEEE International Symposium on Robotic and Sensors Environments (ROSE2011), Montreal, QC, pp. 7–12 (September 2011)

    Google Scholar 

  9. Zhang, H., Martin, F.: Robotic mapping assisted by local magnetic field anomalies. In: Proc. IEEE International Conference on Technologies for Practical Robot Applications (TePRA 2011), Woburn, MA, pp. 25–30 (April 2011)

    Google Scholar 

  10. Vallivaara, I., Haverinen, J., Kemppainen, A., Roning, J.: Magenetic field-based SLAM method for solving the localization problem in mobile robot floor-cleaning task. In: Proc. IEEE International Conference on Advanced Robotics (ICAR2011), Tallinn, Estonia, pp. 198–203 (June 2011)

    Google Scholar 

  11. Frassl, M., Angermann, M., Lichtenstern, M., Robertson, P., Julian, B., Doniec, M.: Magnetic maps of indoor environments for precise localization of legged and non-legged locomotion. In: Proc. IEEE/RSJ International Conference on Intelligent Robots and Systems (IROS 2013), Tokyo, Japan, pp. 913–920 (November 2013)

    Google Scholar 

  12. Jung, J., Lee, S., Myung, H.: Indoor mobile robot localization using ambient magnetic fields and radio sources. In: Proc. International Conference on Robot Intelligence Technology (RiTA 2013), Denver, USA (December 2013)

    Google Scholar 

  13. Gozick, B., Subbu, K., Dantu, R., Maeshiro, T.: Magnetic maps for indoor navigation. IEEE Trans. Instrum. Meas. 60(12), 3883–3891 (2011)

    Article  Google Scholar 

  14. Angermann, M., Frassl, M., Doniecy, M., Julianyz, B., Robertson, P.: Characterization of the indoor magnetic field for applications in localization and mapping. In: Proc. IEEE International Conference on Indoor Positioning and Indoor Navigation (IPIN2012), Sydney, NSW, pp. 1–9 (November 2012)

    Google Scholar 

  15. Cha, S.: Comprehensive survey on distance/similarity measures between probability density functions. International Journal of Mathematical Models and Methods in Applied Sciences 1(4), 300–307 (2007)

    MathSciNet  Google Scholar 

Download references

Author information

Authors and Affiliations

Authors

Editor information

Editors and Affiliations

Rights and permissions

Reprints and permissions

Copyright information

© 2015 Springer International Publishing Switzerland

About this paper

Cite this paper

Jung, J., Myung, H. (2015). Pose-Sequence-Based Graph Optimization Using Indoor Magnetic Field Measurements. In: Kim, JH., Yang, W., Jo, J., Sincak, P., Myung, H. (eds) Robot Intelligence Technology and Applications 3. Advances in Intelligent Systems and Computing, vol 345. Springer, Cham. https://doi.org/10.1007/978-3-319-16841-8_66

Download citation

  • DOI: https://doi.org/10.1007/978-3-319-16841-8_66

  • Publisher Name: Springer, Cham

  • Print ISBN: 978-3-319-16840-1

  • Online ISBN: 978-3-319-16841-8

  • eBook Packages: EngineeringEngineering (R0)

Publish with us

Policies and ethics