Skip to main content
SpringerLink
Log in

Towards Exploiting the Advantages of Colour in Scan Matching

  • Conference paper
ROBOT2013: First Iberian Robotics Conference

Part of the book series: Advances in Intelligent Systems and Computing ((AISC,volume 253))

Abstract

Colour plays an important role in the perception systems of the human beings. In robotics, the development of new sensors has made it possible to obtain colour information together with depth information about the environment. The exploitation of this type of information has become more and more important in numerous tasks. In our recent work, we have developed an evolutionary-based scan matching method. The aim of this work is to modify this method by the introduction of colour properties, taking the first steps in studying how to use colour to improve the scan matching. In particular, we have applied a colour transition detection method based on the delta E divergence between neighbours in a scan. Our algorithm has been tested in a real environment and significant conclusions have been reached.

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

Access this chapter

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

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.

References

  1. Leonard, J.J., Durrant-Whyte, H.: Mobile Robot Localization by Tracking Geometric Beacons. IEEE Transaction on Robotics and Automation 7, 376–382 (1991)

    Article  Google Scholar 

  2. Smith, R., Self, M., Cheeseman, P.: Estimating Uncertain Spatial Relationships in Robotics. In: Proceedings of the Second Conference Annual Conference on Uncertainty in Artificial Intelligence (UAI 1986), New York, NY, pp. 267–288. Elsevier Science (1986)

    Google Scholar 

  3. Martín, F., Triebel, R., Moreno, L., Siegwart, R.: Two different tools for three-dimensional mapping: DE-based scan matching and feature-based loop detection. Robotica (2013)

    Google Scholar 

  4. Storn, R., Price, K.: Differential Evolution – A Simple and Efficient Heuristic for Global Optimization over Continuous Spaces. Journal of Global Optimization 11, 341–359 (1997)

    Article  MathSciNet  MATH  Google Scholar 

  5. Henry, P., Krainin, M., Herbst, E., Ren, X., Fox, D.: RGB-D Mapping: Using Depth Cameras for Dense 3D Modeling of Indoor Environments. In: Proceedings of the Intl. Symp. on Experimental Robotics, ISER (2010)

    Google Scholar 

  6. Nüchter, A., Lingemann, K., Hertzberg, J.: 6D SLAM-3D Mapping Outdoor Environments. Journal of Field Robotics 24, 699–722 (2007)

    Article  MATH  Google Scholar 

  7. Besl, P.J., McKay, N.D.: A method for registration of 3d shapes. IEEE Transactions on Pattern Analysis and Machine Intelligence 14(2), 239–256 (1992)

    Article  Google Scholar 

  8. Hähnel, D., Burgard, W., Thrun, S.: Learning compact 3d models of indoor and outdoor environments with a mobile robot. Robotics and Autonomous Systems 44, 15–27 (2003)

    Article  Google Scholar 

  9. Triebel, R., Pfaff, P., Burgard, W.: Multi-Level Surface Maps for Outdoor Terrain Mapping and Loop Closing. In: Proceedings of the IEEE/RSJ International Conference on Intelligent Robots and Systems, IROS 2006 (2006)

    Google Scholar 

  10. Cole, D.M., Newman, P.M.: Using Laser Range Data for 3D SLAM in Outdoor Environments. In: Proceedings of the IEEE International Conference on Robotics and Automation, ICRA 2006 (2006)

    Google Scholar 

  11. Magnusson, M., Ducket, T.: A Comparison of 3D Registration Algorithms for Autonomous Underground Mining Vehicles. In: Proceedings of the Second European Conference on Mobile Robotics, Ancona, Italy (2005)

    Google Scholar 

  12. Biber, P., Straßer, W.: The Normal Distributions Transform: A New Approach to Laser Scan Matching. In: Proceedings of the IEEE/RSJ International Conference on Intelligent Robots and Systems, IROS 2003 (2003)

    Google Scholar 

  13. Lu, F., Milios, E.: Robot Pose Estimation in Unknown Environments by Matching 2D Range Scans. Journal of Intelligent and Robotic Systems 20, 249–275 (1997)

    Article  Google Scholar 

  14. Tomono, M.: A scan matching method using euclidean invariant signature for global localization and map building. In: Proceedings of the IEEE International Conference on Robotics and Automation, ICRA 2004 (2004)

    Google Scholar 

  15. Zhang, Z.: Iterative point matching for registration of free-form curves and surfaces. International Journal of Computer Vision 13, 119–152 (1994)

    Article  Google Scholar 

  16. Rusinkiewicz, S., Levoy, M.: Efficient Variants of the ICP Algorithm. In: Proceedings of the Third International Conference on 3D Digital Imaging and Modeling (2001)

    Google Scholar 

  17. Bosse, M., Zlot, R.: Map Matching and Data Association for Large-Scale 2D Laser Scan-Based SLAM. The International Journal of Robotics Research 27, 667–691 (2008)

    Article  Google Scholar 

  18. Johnson, A., Kang, S.B.: Registration and integration of textured 3-d data. In: International Conference on Recent Advances in 3-D Digital Imaging and Modeling (3DIM 1997) (1997)

    Google Scholar 

  19. May, S., Droeschel, D., Holz, D., Fuchs, S., Malis, E., Nüchter, A., Hertzberg, J.: Three-dimensional mapping with time-of-flight camers. Journal of Field Robotics 26, 11–12 (2009)

    Article  Google Scholar 

  20. Diosi, A., Kleeman, L.: Laser Scan Matching in Polar Coordinates with Application to SLAM. In: Proceedings of the IEEE/RSJ International Conference on Intelligent Robots and Systems, IROS 2005 (2005)

    Google Scholar 

  21. Thrun, S., Burgard, W., Fox, D.: A real-time algorithm for mobile robot mapping with applications to multi-robot and 3D mapping. In: Proceedings of the IEEE International Conference on Robotics and Automation, ICRA 2000 (2000)

    Google Scholar 

  22. Ramos, F., Fox, D., Durrant-Whyte, H.: CRF-matching: Conditional random fields for feature-based scan matching. In: Proceedings of Robotics: Science and Systems, RSS 2007 (2007)

    Google Scholar 

  23. Izadi, S., Kim, D., Molyneaux, O.H.D., Newcombe, R., Kohli, P., Shotton, J., Hodges, S., Freeman, D., Davison, A., Fitzgibbon, A.: KinectFusion: Real-time 3D Reconstruction and Interaction Using a Moving Depth Camera. In: Proceedings of the 24th Annual ACM Symposium on User Interface Software and Technology (UIST 2011), pp. 559–568 (2011)

    Google Scholar 

  24. Newcombe, R.A., Davison, A.J., Izadi, S., Kohli, P., Hilliges, O., Shotton, J., Hodges, D.M.S., Kim, D., Fitzgibbon, A.: KinectFusion: Real-Time Dense Surface Mapping and Tracking. In: Proceedings of the 10th IEEE International Symposium on Mixed and Augmented Reality, ISMAR 2011 (2011)

    Google Scholar 

  25. Hunter, R.S.: Photoelectric color-difference meter. In: Proceedings of the Winter Meeting of the Optical Society of America (1948)

    Google Scholar 

  26. Hunter, R.S.: Accuracy, precision, and stability of new photo-electric color-difference meter. In: Proceedings of the Thirty-Third Annual Meeting of the Optical Society of America (1948)

    Google Scholar 

  27. Moreno, L., Garrido, S., Mun̈oz, M.L.: Evolutionary Filter for Robust Mobile Robot Localization. Robotics and Autonomous Systems 54(7), 590–600 (2006)

    Article  Google Scholar 

  28. Martín, F., Moreno, L., Garrido, S., Blanco, D.: High-Accuracy Global Localization Filter for three-dimensional Environments. Robotica 30, 363–378 (2011)

    Article  Google Scholar 

  29. Magnusson, M., Nüchter, A., Lörken, C., Lilienthal, A.J., Hertzberg, J.: Evaluation of 3D Registration Reliability and Speed – A Comparison of ICP and NDT. In: Proceedings of the IEEE International Conference on Robotics and Automation, ICRA 2009 (2009)

    Google Scholar 

Download references

Author information

Authors and Affiliations

  1. Carlos III University, Madrid, Spain

    Fernando Martín & Luis Moreno

  2. University of Technology, Sydney, Australia

    Jaime Valls Miró

Authors
  1. Fernando Martín
    View author publications

    You can also search for this author in PubMed Google Scholar

  2. Jaime Valls Miró
    View author publications

    You can also search for this author in PubMed Google Scholar

  3. Luis Moreno
    View author publications

    You can also search for this author in PubMed Google Scholar

Corresponding author

Correspondence to Fernando Martín .

Editor information

Editors and Affiliations

  1. CAR UPM-CSIC, Agencia Estatal Consejo Superior de Investigaciones Científicas (CSIC), Arganda del Rey, Spain

    Manuel A. Armada

  2. Universitat Politècnica de Catalunya (UPC), Barcelona, Spain

    Alberto Sanfeliu

  3. Universidad Politécnica de Madrid (UPM), Madrid, Spain

    Manuel Ferre

Rights and permissions

Reprints and permissions

Copyright information

© 2014 Springer International Publishing Switzerland

About this paper

Cite this paper

Martín, F., Valls Miró, J., Moreno, L. (2014). Towards Exploiting the Advantages of Colour in Scan Matching. In: Armada, M., Sanfeliu, A., Ferre, M. (eds) ROBOT2013: First Iberian Robotics Conference. Advances in Intelligent Systems and Computing, vol 253. Springer, Cham. https://doi.org/10.1007/978-3-319-03653-3_17

Download citation

  • DOI: https://doi.org/10.1007/978-3-319-03653-3_17

  • Publisher Name: Springer, Cham

  • Print ISBN: 978-3-319-03652-6

  • Online ISBN: 978-3-319-03653-3

  • eBook Packages: EngineeringEngineering (R0)

Publish with us

Policies and ethics

Search

Navigation