Skip to main content
SpringerLink
Log in
Book cover

Mapping, Planning and Exploration with Pose SLAM pp 7–24Cite as

SLAM Front-End

  • Chapter
  • First Online:

  • 2728 Accesses

Part of the book series: Springer Tracts in Advanced Robotics ((STAR,volume 119))

Abstract

In this Chapter we discuss our choice of front-end for SLAM, the part in charge of processing the sensor information to generate the observations that will be fed to the estimation machinery.

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   99.00
Price excludes VAT (USA)
  • Available as EPUB and PDF
  • Read on any device
  • Instant download
  • Own it forever
Softcover Book
USD   129.99
Price excludes VAT (USA)
  • Compact, lightweight edition
  • Dispatched in 3 to 5 business days
  • Free shipping worldwide - see info
Hardcover Book
USD   129.99
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

References

  1. P.J. Besl, N.D. McKay, A method for registration of 3D shapes. IEEE Trans. Pattern Anal. Mach. Intell. 14(2), 239–256 (1992). Feb

    Article  Google Scholar 

  2. D. Scaramuzza, F. Fraundorfer, Visual odometry: Part I—the first 30 years and fundamentals. Robot. Automat. Mag. 18(4), 80–92 (2011). Dec

    Article  Google Scholar 

  3. F. Fraundorfer, D. Scaramuzza, Visual odometry: Part II—matching, robustness, and applications. Robot. Automat. Mag. 19(2), 78–90 (2012)

    Article  Google Scholar 

  4. V. Ila, J. Andrade-Cetto, R. Valencia, A. Sanfeliu, Vision-based loop closing for delayed state robot mapping, in Proceedings of IEEE/RSJ International Conference on Intelligent Robots Systems (San Diego, 2007), pp. 3892–3897

    Google Scholar 

  5. D.G. Lowe, Distinctive image features from scale-invariant keypoints. Int. J. Comput. Vis. 60(2), 91–110 (2004). Nov

    Article  Google Scholar 

  6. M. Fischler, R. Bolles, Random sample consensus: A paradigm for model fitting with applications to image analysis and automated cartography. Comm. ACM 24, 381–385 (1981)

    Article  MathSciNet  Google Scholar 

  7. O. Faugeras, Three-Dimensional Computer Vision: A Geometric Viewpoint (The MIT Press, Cambridge, 1993)

    Google Scholar 

  8. C.G. Harris, M. Stephens, A combined corner edge detector, in Proceedings of Alvey Vision Conference (Manchester, 1988), pp. 189–192

    Google Scholar 

  9. J. Shi, C. Tomasi, Good features to track, in Proceedings of 9th IEEE Conference on Computer Vision and Pattern Recognition (Seattle, 1994), pp. 593–600

    Google Scholar 

  10. A.J. Davison, I.D. Reid, N.D. Molton, O. Stasse, MonoSLAM: Real-time single camera SLAM. IEEE Trans. Pattern Anal. Mach. Intell. 26(6), 1052–1067 (2007)

    Article  Google Scholar 

  11. K. Mikolajczyk, C. Schmid, A performance evaluation of local descriptors. IEEE Trans. Pattern Anal. Mach. Intell. 27(10), 1615–1630 (2005)

    Article  Google Scholar 

  12. R. Hartley, A. Zisserman, Multiple View Geometry in Computer Vision (Cambridge University Press, Cambridge, 2000)

    MATH  Google Scholar 

  13. B.K.P. Horn, H.M. Hilden, S. Negahdaripour, Closed-form solution of absolute orientation using orthonormal matrices. J. Opt. Soc. Am. A 5(7), 1127–1135 (1988)

    Article  MathSciNet  Google Scholar 

  14. K.S. Arun, T.S. Huang, S.D. Blostein, Least-squares fitting of two 3-D point sets. IEEE Trans. Pattern Anal. Mach. Intell. 9(5), 698–700 (1987). Sep

    Article  Google Scholar 

  15. L. Matthies, S. Shafer, Error modeling in stereo navigation. IEEE J. Robot. Autom. 3(3), 239–248 (1987). Jun

    Article  Google Scholar 

  16. Y. Bar-Shalom, X. Rong Li, T. Kirubarajan, Estimation with Applications to Tracking and Navigation (Wiley, New York, 2001)

    Google Scholar 

  17. A. Censi, An accurate closed-form estimate of ICP’s covariance, in Proceedings of the IEEE International Conference on Robotics and Automation (Rome, 2007), pp. 3167–3172

    Google Scholar 

  18. D. Nister, O. Naroditsky, J. Bergen, Visual odometry, in Proceedings of 18th IEEE Conference on Computer Vision and Pattern Recognition (Washington, 2004), pp. 652–659

    Google Scholar 

  19. H.P. Moravec, Obstacle avoidance and navigation in the real world by a seeing robot rover. Ph.D. thesis, Stanford University, California, 1980

    Google Scholar 

  20. H.C. Longuet-Higgins, A computer program for reconstructing a scene from two projections. Nature 293(11), 133–135 (1981)

    Article  Google Scholar 

  21. C. Olson, L. Matthies, M. Schoppers, M. Maimone, Robust stereo ego-motion for long distance navigation, in Proceedings of 14th IEEE Conference on Computer Vision and Pattern Recognition, vol. 2 (Hilton Head, SC, 2000), pp. 453–458

    Google Scholar 

  22. C. Olson, L. Matthies, M. Schoppers, M. Maimone, Rover navigation using stereo ego-motion. Robot. Auton. Syst. 43(4), 215–229 (2003)

    Article  Google Scholar 

  23. Y. Cheng, M. Maimone, L. Matthies, Visual odometry on the mars exploration rovers—a tool to ensure accurate driving and science imaging. Robot. Automat. Mag. 13(2), 54–62 (2006)

    Article  Google Scholar 

  24. M. Maimone, Y. Cheng, L. Matthies, Two years of visual odometry on the mars exploration rovers. J. Field Robot. 24(3), 169–186 (2007)

    Article  Google Scholar 

  25. A. Milella, R. Siegwart, Real-time scattering compensation for time-of-flight camera, in International Conference on Computer Vision Systems (2006), pp. 21–24

    Google Scholar 

  26. S. Lacroix, A. Mallet, R. Chatila, L. Gallo, Real-time scattering compensation for time-of-flight camera, in Proceedings of International Symposium on Artificial Intelligence, Robotics and Automation in Space (Noordwijk, 1999), pp. 433–440

    Google Scholar 

  27. S. Se, D. Lowe, J. Little, Mobile robot localization and mapping with uncertainty using scale-invariant visual landmarks. Int. J. Robot. Res. 21(8), 735–758 (2002). Aug

    Article  Google Scholar 

  28. S. Se, D. Lowe, J. Little, Vision-based global localization and mapping for mobile robots. IEEE Trans. Rob. 21(3), 364–375 (2005). Jun

    Article  Google Scholar 

  29. K. Konolige, M. Agrawal, J. Solà, Large scale visual odometry for rough terrain, in Proceedings of 13th International Symposium of Robotics Research (Hiroshima, 2007)

    Google Scholar 

  30. L. Kneip, M. Chli, R. Siegwart, Robust real-time visual odometry with a single camera and an IMU, in Proceedings of British Machine Vision Conference (BMVA Press, Dundee, 2011), pp. 20.1–20.10

    Google Scholar 

  31. M. Calonder, V. Lepetit, C. Strecha, P. Fua, BRIEF: binary robust independent elementary features, in Proceedings of 11th European Conference on Computer Vision (2010), pp. 778–792

    Google Scholar 

  32. T. Kazik, L. Kneip, J. Nikolic, M. Pollefeys, R. Siegwart, Real-time 6D stereo visual odometry with non-overlapping fields of view, in IEEE Conference on Computer Vision and Pattern Recognition (Providence, 2012), pp. 1529–1536

    Google Scholar 

  33. A.R. Chowdhury, R. Chellappa, Statistical error propagation in 3D modeling from monocular video, in IEEE CVPR Workshops (Madison, 2003)

    Google Scholar 

  34. A.R. Chowdhury, R. Chellappa, Stochastic approximation and rate-distortion analysis for robust structure and motion estimation. Int. J. Comput. Vis. 55(1), 27–53 (2003)

    Article  Google Scholar 

  35. P. Zhang, J. Gu, E. Milios, Registration uncertainty for robot self-localization in 3D, in Proceedings of 2nd Canadian Conference on Computer and Robot Vision (Victoria, 2005), pp. 490–497

    Google Scholar 

  36. J. Borenstein, L. Feng, Measurement and correction of systematic odometry errors in mobile robots. IEEE Trans. Rob. 12(6), 869–880 (1996). Dec

    Article  Google Scholar 

  37. A. Martinelli, The odometry error of a mobile robot with a synchronous drive system. IEEE Trans. Rob. 18(3), 399–405 (2002). Jun

    Article  Google Scholar 

  38. J.M. Mirats, J.L. Gordillo, C.A. Borja, A closed-form expression for the uncertainty in odometry position estimate of an autonomous vehicle. IEEE Trans. Rob. 21(5), 1017–1022 (2005). Oct

    Article  Google Scholar 

  39. S. Foix, G. Alenyà, J. Andrade-Cetto, C. Torras, Object modeling using a ToF camera under an uncertainty reduction approach, in Proceedings of IEEE International Conference on Robotics and Automation (Anchorage, 2010), pp. 1306–1312

    Google Scholar 

Download references

Author information

Authors and Affiliations

  1. Carnegie Mellon University, Pittsburgh, PA, USA

    Rafael Valencia

  2. CSIC-UPC, Institut de Robòtica i Informàtica Industrial, Barcelona, Spain

    Juan Andrade-Cetto

Authors
  1. Rafael Valencia
    View author publications

    You can also search for this author in PubMed Google Scholar

  2. Juan Andrade-Cetto
    View author publications

    You can also search for this author in PubMed Google Scholar

Corresponding author

Correspondence to Rafael Valencia .

Rights and permissions

Reprints and permissions

Copyright information

© 2018 Springer International Publishing AG

About this chapter

Cite this chapter

Valencia, R., Andrade-Cetto, J. (2018). SLAM Front-End. In: Mapping, Planning and Exploration with Pose SLAM. Springer Tracts in Advanced Robotics, vol 119. Springer, Cham. https://doi.org/10.1007/978-3-319-60603-3_2

Download citation

  • DOI: https://doi.org/10.1007/978-3-319-60603-3_2

  • Published:

  • Publisher Name: Springer, Cham

  • Print ISBN: 978-3-319-60602-6

  • Online ISBN: 978-3-319-60603-3

  • eBook Packages: EngineeringEngineering (R0)

Publish with us

Policies and ethics

Search

Navigation