Skip to main content

A Version of Libviso2 for Central Dioptric Omnidirectional Cameras with a Laser-Based Scale Calculation

  • Conference paper
  • First Online:
Book cover Robot 2019: Fourth Iberian Robotics Conference (ROBOT 2019)

Part of the book series: Advances in Intelligent Systems and Computing ((AISC,volume 1092))

Included in the following conference series:

Abstract

Monocular Visual Odometry techniques represent a challenging and appealing research area in robotics navigation field. The use of a single camera to track robot motion is a hardware-cheap solution. In this context, there are few Visual Odometry methods on the literature that estimate robot pose accurately using a single camera without any other source of information. The use of omnidirectional cameras in this field is still not consensual. Many works show that for outdoor environments the use of them does represent an improvement compared with the use of conventional perspective cameras. Besides that, in this work we propose an open-source monocular omnidirectional version of the state-of-the-art method Libviso2 that outperforms the original one even in outdoor scenes. This approach is suitable for central dioptric omnidirectional cameras and takes advantage of their wider field of view to calculate the robot motion with a really positive performance on the context of monocular Visual Odometry. We also propose a novel approach to calculate the scale factor that uses matches between laser measures and 3-D triangulated feature points to do so. The novelty of this work consists in the association of the laser ranges with the features on the omnidirectional image. Results were generate using three open-source datasets built in-house showing that our unified system largely outperforms the original monocular version of Libviso2.

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

Access this chapter

Chapter
USD 29.95
Price excludes VAT (USA)
  • Available as PDF
  • Read on any device
  • Instant download
  • Own it forever
eBook
USD 129.00
Price excludes VAT (USA)
  • Available as EPUB and PDF
  • Read on any device
  • Instant download
  • Own it forever
Softcover Book
USD 169.99
Price excludes VAT (USA)
  • Compact, lightweight 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

Institutional subscriptions

Notes

  1. 1.

    https://github.com/srv/viso2.

  2. 2.

    https://bit.ly/2IzXwow.

  3. 3.

    https://github.com/srv/viso2.

References

  1. Aguiar, A., Sousa, A., Santos, F., Oliveira, M.: Monocular visual odometry benchmarking and turn performance optimization. In: 19th IEEE International Conference on Autonomous Robot Systems and Competitions, April 2019

    Google Scholar 

  2. Caruso, D., Engel, J., Cremers, D.: Large-scale direct SLAM for omnidirectional cameras. In: IEEE/RSJ International Conference on Intelligent Robots and Systems (IROS). IEEE, September 2015

    Google Scholar 

  3. Geiger, A., Ziegler, J., Stiller, C.: StereoScan: Dense 3D reconstruction in real-time. In: IEEE Intelligent Vehicles Symposium (IV). IEEE, June 2011

    Google Scholar 

  4. Giubilato, R., Chiodini, S., Pertile, M., Debei, S.: Scale correct monocular visual odometry using a lidar altimeter. In: IEEE/RSJ International Conference on Intelligent Robots and Systems (IROS), pp. 3694–3700, October 2018

    Google Scholar 

  5. Gräter, J., Wilczynski, A., Lauer, M.: LIMO: lidar-monocular visual odometry. CoRR abs/1807.07524 (2018). http://arxiv.org/abs/1807.07524

  6. Kohlbrecher, S., von Stryk, O., Meyer, J., Klingauf, U.: A flexible and scalable slam system with full 3D motion estimation. In: IEEE International Symposium on Safety, Security, and Rescue Robotics, pp. 155–160, November 2011

    Google Scholar 

  7. Matsuki, H., von Stumberg, L., Usenko, V., Stueckler, J., Cremers, D.: Omnidirectional DSO: Direct sparse odometry with fisheye cameras. In: IEEE Robotics and Automation Letters (RA-L) & International Conference on Intelligent Robots and Systems (IROS) (2018)

    Google Scholar 

  8. Raju, V.K.T.P.: Fisheye camera calibration and applications. Master’s thesis, Arizona State University (2014)

    Google Scholar 

  9. Reis, R., Mendes, J., Neves dos Santos, F., Morais, R., Ferraz, N., Santos, L., Sousa, A.: Redundant robot localization system based in wireless sensor network. In: IEEE International Conference on Autonomous Robot Systems and Competitions (ICARSC), pp. 154–159, April 2018

    Google Scholar 

  10. Rituerto, A., Puig, L., Guerrero, J.J.: Comparison of omnidirectional and conventional monocular systems for visual SLAM

    Google Scholar 

  11. Santos, L., Ferraz, N., Neves dos Santos, F., Mendes, J., Morais, R., Costa, P., Reis, R.: Path planning aware of soil compaction for steep slope vineyards. In: IEEE International Conference on Autonomous Robot Systems and Competitions (ICARSC), pp. 250–255, April 2018

    Google Scholar 

  12. Scaramuzza, D., Martinelli, A., Siegwart, R.: A flexible technique for accurate omnidirectional camera calibration and structure from motion. In: Fourth IEEE International Conference on Computer Vision Systems (ICVS 2006). IEEE (2006)

    Google Scholar 

  13. Scaramuzza, D., Fraundorfer, F.: Visual odometry [tutorial]. IEEE Robot. Autom. Mag. 18(4), 80–92 (2011)

    Article  Google Scholar 

  14. Scaramuzza, D., Martinelli, A., Siegwart, R.: A toolbox for easily calibrating omnidirectional cameras. In: IEEE/RSJ International Conference on Intelligent Robots and Systems. IEEE, October 2006

    Google Scholar 

  15. Tardif, J.P., Pavlidis, Y., Daniilidis, K.: Monocular visual odometry in urban environments using an omnidirectional camera. In: IEEE/RSJ International Conference on Intelligent Robots and Systems. IEEE, September 2008

    Google Scholar 

  16. Wu, K., Di, K., Sun, X., Wan, W., Liu, Z.: Enhanced monocular visual odometry integrated with laser distance meter for astronaut navigation. Sensors 14, 4981–5003 (2014)

    Article  Google Scholar 

  17. Zhang, Z., Rebecq, H., Forster, C., Scaramuzza, D.: Benefit of large field-of-view cameras for visual odometry. In: IEEE International Conference on Robotics and Automation (ICRA). IEEE, May 2016

    Google Scholar 

Download references

Acknowledgment

This work is co-financed by the European Regional Development Fund (ERDF) through the Interreg V-A Espanha-Portugal Programme (POCTEP) 2014–2020 within project 0095_BIOTECFOR_1_P. This work also was co-financed by the ERDF European Regional Development Fund through the Operational Programme for Competitiveness and Internationalisation - COMPETE 2020 under the PORTUGAL 2020 Partnership Agreement, and through the Portuguese National Innovation Agency (ANI) as a part of project “ROMOVI: POCI-01-0247-FEDER-017945” The opinions included in this paper shall be the sole responsibility of their authors. The European Commission and the Authorities of the Programme aren’t responsible for the use of information contained therein.

Author information

Authors and Affiliations

Authors

Corresponding author

Correspondence to André Aguiar .

Editor information

Editors and Affiliations

Rights and permissions

Reprints and permissions

Copyright information

© 2020 Springer Nature Switzerland AG

About this paper

Check for updates. Verify currency and authenticity via CrossMark

Cite this paper

Aguiar, A., Santos, F., Santos, L., Sousa, A. (2020). A Version of Libviso2 for Central Dioptric Omnidirectional Cameras with a Laser-Based Scale Calculation. In: Silva, M., Luís Lima, J., Reis, L., Sanfeliu, A., Tardioli, D. (eds) Robot 2019: Fourth Iberian Robotics Conference. ROBOT 2019. Advances in Intelligent Systems and Computing, vol 1092. Springer, Cham. https://doi.org/10.1007/978-3-030-35990-4_11

Download citation

Publish with us

Policies and ethics