Skip to main content

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

  • 2994 Accesses

Abstract

The SLAM problem has been traditionally addressed as a state estimation problem in which perception and motion uncertainties are coupled.

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 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

Institutional subscriptions

References

  1. M.W.M.G. Dissanayake, P. Newman, S. Clark, H.F. Durrant-Whyte, M. Csorba, A solution to the simultaneous localization and map building (SLAM) problem. IEEE Trans. Robot. Autom. 17(3), 229–241 (2001)

    Article  Google Scholar 

  2. R.C. Smith, P. Cheeseman, On the representation and estimation of spatial uncertainty. Int. J. Robot. Res. 5(4), 56–68 (1986)

    Article  Google Scholar 

  3. J. Andrade-Cetto, A. Sanfeliu, The effects of partial observability when building fully correlated maps. IEEE Trans. Robot. 21(4), 771–777 (2005)

    Article  Google Scholar 

  4. J. Andrade-Cetto, A. Sanfeliu, Environment Learning for Indoor Mobile Robots. A Stochastic State Estimation Approach to Simultaneous Localization and Map Building, Springer Tracts in Advanced Robotics, vol. 23 (Springer, 2006)

    Google Scholar 

  5. S. Thrun, Y. Liu, D. Koller, A.Y. Ng, Z. Ghahramani, H. Durrant-Whyte, Simultaneous localization and mapping with sparse extended information filters. Int. J. Robot. Res. 23(7–8), 693–716 (2004)

    Article  Google Scholar 

  6. R.M. Eustice, H. Singh, J.J. Leonard, Exactly sparse delayed-state filters for view-based SLAM. IEEE Trans. Robot. 22(6), 1100–1114 (2006)

    Article  Google Scholar 

  7. 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 and Systems (San Diego, Nov 2007), pp. 3892–3897

    Google Scholar 

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

    Article  Google Scholar 

  9. M. Montemerlo, S. Thrun, FastSLAM: A Scalable Method for the Simultaneous Localization and Mapping Problem in Robotics, Springer Tracts in Advanced Robotics, vol. 27 (Springer, 2007)

    Google Scholar 

  10. F. Dellaert, M. Kaess, Square root SAM: simultaneous localization and mapping via square root information smoothing. Int. J. Robot. Res. 25(12), 1181–1204 (2006)

    Article  MATH  Google Scholar 

  11. V. Ila, J.M. Porta, J. Andrade-Cetto, Information-based compact Pose SLAM. IEEE Trans. Robot. 26(1), 78–93 (2010)

    Article  Google Scholar 

  12. K. Konolige, M. Agrawal, FrameSLAM: from bundle adjustment to realtime visual mapping. IEEE Trans. Robot. 24(5), 1066–1077 (2008)

    Article  Google Scholar 

  13. S.J. Julier, J.K. Uhlmann, A counter example to the theory of simultaneous localization and map building, in Proceedings of IEEE International Conference on Robotics and Automation (Seoul, May 2001), pp. 4238–4243

    Google Scholar 

  14. T. Bailey, J. Nieto, J. Guivant, M. Stevens, E. Nebot, Consistency of the EKF-SLAM algorithm, in Proceedings of IEEE/RSJ International Conference on Intelligent Robots and Systems (Beijing, Oct 2006), pp. 3562–3568

    Google Scholar 

  15. A. Sanfeliu, J. Andrade-Cetto, Ubiquitous networking robotics in urban settings, in Proceedings of IEEE/RSJ IROS Workshop on Network Robots and Systems (Beijing, Oct 2006), pp. 14–18

    Google Scholar 

  16. R. Smith, M. Self, P. Cheeseman, Estimating uncertain spatial relationships in robotics, in Autonomous Robot Vehicles (1990), pp. 167–193

    Google Scholar 

  17. K.L. Ho, P. Newman, Detecting loop closure with scene sequences. Int. J. Comput. Vis. 74(3), 261–286 (2007)

    Article  Google Scholar 

  18. M. Cummins, P. Newman, FAB-MAP: Probabilistic localization and mapping in the space of appearance. Int. J. Robot. Res. 27(6), 647–665 (2008)

    Article  Google Scholar 

  19. P. Newman, D. Cole, K. Ho, Outdoor SLAM using visual appearance and laser ranging, in Proceedings of IEEE International Conference on Robotics and Automation (Orlando, May 2006), pp. 1180–1187

    Google Scholar 

  20. K. Fukunaga, Introduction to Statistical Pattern Recognition, 2nd edn. (Academic Press, San Diego, 1990)

    MATH  Google Scholar 

  21. G. Dissanayake, S.B. Williams, H. Durrant-Whyte, T. Bailey, Map management for efficient simultaneous localization and mapping (SLAM). Auton. Robot. 12(3), 267–286 (2002)

    Article  MATH  Google Scholar 

  22. T. Vidal-Calleja, A.J. Davison, J. Andrade-Cetto, D.W. Murray, Active control for single camera SLAM, in Proceedings of IEEE International Conference on Robotics and Automation (Orlando, May 2006), pp. 1930–1936

    Google Scholar 

  23. R. Sim, Stable exploration for bearings-only SLAM. in Proceedings of IEEE International Conference on Robotics and Automation (Barcelona, Apr 2005), pp. 2422–2427

    Google Scholar 

  24. W. Zhou, J.V. Miro, G. Dissanayake, Information-driven 6D SLAM based on ranging vision, in Proceedings of IEEE/RSJ IROS Workshop on Network Robots and Systems (Nice, Sep 2008), pp. 2072–2077

    Google Scholar 

  25. H. Kretzschmar, C. Stachniss, G. Grisetti, Efficient information-theoretic graph pruning for graph-based SLAM with laser range finders, in Proceedings of IEEE/RSJ IROS Workshop on Network Robots and Systems (San Francisco, Sep 2011), pp. 865–871

    Google Scholar 

  26. Y. Ma, S. Soatto, J. Kosecka, S.S. Sastry. An Invitation to 3-d Vision (Springer, 2004)

    Google Scholar 

  27. E.H. Teniente, J. Andrade-Cetto, FaMSA: Fast multi-scan alignment with partially known correspondences, in Proceedings of European Conference on Mobile Robotics (Orebro, Sep 2011), pp. 139–144

    Google Scholar 

  28. 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, May 2010), pp. 1306–1312

    Google Scholar 

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

    Google Scholar 

  30. R. Valencia, E.H. Teniente, E. Trulls, J. Andrade-Cetto, 3D mapping for urban service robots, in Proceedings of IEEE/RSJ International Conference on Intelligent Robots and Systems (Saint Louis, Oct 2009), pp. 3076–3081

    Google Scholar 

  31. R. Smith, M. Self, P. Cheeseman, A stochastic map for uncertain spatial relationships, in Proceedings of 4th International Symposium on Robotics Research (Santa Clara, 1988), pp. 467–474

    Google Scholar 

  32. H.F. Durrant-Whyte, Uncertain geometry in robotics. IEEE J. Robot. Autom. 4(1), 23–31 (1988)

    Article  Google Scholar 

  33. R. Chatila, J. Lauomnd, Position referencing and consistent world modeling for mobile robots, in Proceedings of IEEE International Conference on Robotics and Automation, vol. 2, (St. Louis, Mar 1985) pp. 138–145

    Google Scholar 

  34. J.J. Leonard, H.J.S. Feder, A computationally efficient method for large-scale concurrent mapping and localization, in Proceedings of 9th International Symposium of Robotics Research, eds. by J. Hollerbach, D. Koditschek (Salt Lake City, Nov 1999)

    Google Scholar 

  35. G. Dissanayake, H. Durrant-Whyte, T. Bailey, A computationally efficient solution to the simultaneous localisation and map building (SLAM) problem. In Proceedings of IEEE International Conference on Robotics and Automation (San Francisco, Apr 2000), pp. 1009–1014

    Google Scholar 

  36. H. Durrant-Whyte, S. Majumder, M. de Battista, S. Scheding, A Bayesian algorithm for simultaneous localisation and map building. In Proceedings of 10th International Symposium of Robotics Research (Lorne, Nov 2001)

    Google Scholar 

  37. S. Thrun, Robotic mapping: a survey, in Exploring Artificial Intelligence in the New Millenium, eds. by G. Lakemeyer, B. Nebel. World Scientific Series in Robotics and Intelligent Systems (Morgan Kaufmann, 2002)

    Google Scholar 

  38. H. Durrant-Whyte, T. Bailey, Simultaneous localisation and mapping (SLAM): Part I the essential algorithms. Robot. Autom. Mag. 13(2), 99–110 (2006)

    Article  Google Scholar 

  39. T. Bailey, H. Durrant-Whyte, Simultaneous localisation and mapping (SLAM): Part II state of the art. Robot. Autom. Mag. 13(3), 108–117 (2006)

    Article  Google Scholar 

  40. T. Bailey, Mobile robot localisation and mapping in extensive outdoor environments. Ph.D. thesis, The University of Sydney, Australian Center for Field Robotics, Sydney, 2002

    Google Scholar 

  41. J.D. Tardós, J. Neira, P.M. Newman, J.J. Leonard, Robust mapping and localization in indoor environments using sonar data. Int. J. Robot. Res. 21(4), 311–330 (2002)

    Article  Google Scholar 

  42. J. Andrade-Cetto, T. Vidal-Calleja, A. Sanfeliu, Unscented transformation of vehicle states in SLAM, in Proceedings of IEEE International Conference on Robotics and Automation (Barcelona, Apr 2005), pp. 324–329

    Google Scholar 

  43. R. Martinez-Cantin, J.A. Castellanos, Unscented SLAM for large-scale outdoor environments, in Proceedings of IEEE/RSJ International Conference on Intelligent Robots and Systems (Edmonton, Aug 2005), pp. 328–333

    Google Scholar 

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

    MATH  Google Scholar 

  45. F. Lu, E. Milios, Globally consistent range scan alignment for environment mapping. Auton. Robot. 4(4), 333–349 (1997)

    Article  Google Scholar 

  46. G. Grisetti, C. Stachniss, S. Grzonka, W. Burgard, A tree parameterization for efficiently computing maximum likelihood maps using gradient descent, in Robotics: Science and Systems III (Atlanta, Jun 2007), pp. 9:1–9:8

    Google Scholar 

  47. G. Grisetti, R. Kummerle, C. Stachniss, W. Burgard, A tutorial on Graph-Based SLAM. Intell. Transp. Syst. Mag. 2(4), 31–43 (2010)

    Article  Google Scholar 

  48. J.B. Folkesson, H.I. Christensen, Graphical SLAM–a self-correcting map, in Proceedings of IEEE International Conference on Robotics and Automation (New Orleans, Apr 2004), pp. 383–390

    Google Scholar 

  49. J.B. Folkesson, H.I. Christensen, Closing the loop with graphical SLAM. IEEE Trans. Robot. 23(4), 731–741 (2007)

    Article  Google Scholar 

  50. A. Howard, M. Mataric, G. Sukhatme, Relaxation on a mesh: a formalism for generalized localization, in Proceedings of IEEE/RSJ International Conference on Intelligent Robots and Systems (Maui, Nov 2001), pp. 1055–1060

    Google Scholar 

  51. T. Duckett, S. Marsland, J. Shapiro, Fast, on-line learning of globally consistent maps. Auton. Robot. 12(3), 287–300 (2002)

    Article  MATH  Google Scholar 

  52. U. Frese, P. Larsson, T. Duckett, A multilevel relaxation algorithm for simultaneous localization and mapping. IEEE Trans. Robot. 21(2), 196–207 (2005)

    Article  Google Scholar 

  53. E. Olson, J. Leonard, S. Teller, Fast iterative alignment of pose graphs with poor initial estimates, in Proceedings of IEEE International Conference on Robotics and Automation (Orlando, May 2006), pp. 2262–2269

    Google Scholar 

  54. G. Grisetti, C. Stachniss, W. Burgard, Non-linear constraint network optimization for efficient map learning. IEEE Trans. Intell. Transp. Syst. 10(3), 428–439 (2009)

    Article  Google Scholar 

  55. K. Konolige, G. Grisetti, R. Kuemmerle, W. Burgard, L. Benson, R. Vincent, Psparse pose adjustment for 2d mapping, in Proceedings of IEEE/RSJ International Conference on Intelligent Robots and Systems (Taipei, Oct 2010), pp. 22–29

    Google Scholar 

  56. R. Kummerle, G. Grisetti, H. Strasdat, K. Konolige, W. Burgard, g2o: a general framework for graph optimization, in Proceedings of IEEE International Conference on Robotics and Automation (Shanghai, May 2011), pp. 3607–3613

    Google Scholar 

  57. M. Kaess, H. Johannsson, R. Roberts, V. Ila, J. Leonard, F. Dellaert, iSAM2: incremental smoothing and mapping using the bayes tree. Int. J. Robot. Res. 31(2), 216–235 (2012)

    Article  Google Scholar 

  58. G. Klein, D. Murray, Parallel tracking and mapping for small AR workspaces, in Proceedings of IEEE International Symposium on Mixed and Augmented Reality (Nara, Nov 2007), pp. 225–234

    Google Scholar 

  59. E. Eade, T. Drummond, Monocular SLAM as a graph of coalesced observations, in Proceedings of IEEE International Conference on Computer Vision (Rio de Janeiro, Oct 2007), pp. 1–8

    Google Scholar 

  60. P. Piniés, L.M. Paz, D. Galvez-Lopez, J.D. Tardós, CI-Graph simultaneous localization and mapping for three-dimensional reconstruction of large and complex environments using a multicamera system. J. Field Robot. 27(5), 561–586 (2010)

    Article  Google Scholar 

  61. N. Kai, D. Steedly, F. Dellaert, Tectonic SAM: exact, out-of-core, submap-based SLAM, in Proceedings of IEEE International Conference on Robotics and Automation (Barcelona, Apr 2005), pp. 1678–1685

    Google Scholar 

  62. M. Bosse, P. Newman, J. Leonard, S. Teller, Simultaneous localization and map building in large-scale cyclic environments using the atlas framework. Int. J. Robot. Res. 23(12), 1113–1139 (2004)

    Article  Google Scholar 

  63. G. Sibley, C. Mei, I. Reid, P. Newman, Vast-scale outdoor navigation using adaptive relative bundle adjustment. Int. J. Robot. Res. 29(8), 958–980 (2010)

    Article  Google Scholar 

  64. J. Neira, J.D. Tardós, Data association in stochastic mapping using the joint compatibility test. IEEE Trans. Robot. Autom. 17(6), 890–897 (2001)

    Article  Google Scholar 

  65. J.A. Castellanos, J.M. Martínez, J. Neira, J.D. Tardós, Experiments in multisensor mobile robot localization and map building, in 3rd IFAC Symposium on Intelligent Autonomous Vehicles (Madrid, 1998), pp. 173–178

    Google Scholar 

  66. J. Andrade-Cetto, A. Sanfeliu, Temporal landmark validation in CML, in Proceedings of IEEE International Conference on Robotics and Automation (Taipei, Sep 2003), pp. 1576–1581

    Google Scholar 

  67. N. Sunderhauf, P. Protzel, Switchable constraints for Robust Pose Graph SLAM, in Proceedings of IEEE/RSJ International Conference on Intelligent Robots and Systems (Algarve, Oct 2012), pp. 1879–1884

    Google Scholar 

  68. N. Sunderhauf, P. Protzel, Towards a robust back-end for pose graph SLAM, in Proceedings of IEEE International Conference on Robotics and Automation (Saint Paul, Minessota, May 2012), pp. 1254–1261

    Google Scholar 

  69. P. Agarwal, G. Tipaldi, L. Spinello, C. Stachniss, W. Burgard, Robust map optimization using dynamic covariance scaling, in Proceedings of IEEE International Conference on Robotics and Automation (Karlsruhe, May 2013), pp. 62–69

    Google Scholar 

  70. E. Olson, P. Agarwal, Inference on networks of mixtures for robust robot mapping. Int. J. Robot. Res. 32(7), 826–840 (2013)

    Article  Google Scholar 

  71. Y. Latif, C. Cadena, J. Neira, Robust loop closing over time for pose graph SLAM. Int. J. Robot. Res. 32(14), 1611–1626 (2013)

    Article  Google Scholar 

  72. L. Carlone, A. Censi, F. Dellaert, Selecting good measurements via L1 relaxation: a convex approach for robust estimation over graphs, in Proceedings of IEEE/RSJ International Conference on Intelligent Robots and Systems (Chicago, Sep 2014), pp. 2667–2674

    Google Scholar 

  73. Y. Latif, C. Cadena, J. Neira, Robust graph SLAM back-ends: a comparative analysis, in Proceedings of IEEE/RSJ International Conference on Intelligent Robots and Systems (Chicago, Sep 2014), pp. 2683–2690

    Google Scholar 

  74. N. Sunderhauf, P. Protzel, Switchable Constraints vs. Max-Mixture models vs. RRR-A comparison of three approaches to robust pose graph SLAM, in Proceedings of IEEE International Conference on Robotics and Automation (Karlsruhe, May 2013), pp. 5198–5203

    Google Scholar 

  75. T. Vidal-Calleja, Visual navigation in unknown environments. Ph.D. thesis, UPC, Barcelona, Jul 2007

    Google Scholar 

  76. A. Nüchter, K. Lingemann, J. Hertzberg, H. Surmann, 6D SLAM-3D mapping outdoor environments. J. Field Robot. 24(8–9), 699–722 (2007)

    Article  MATH  Google Scholar 

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

    Article  Google Scholar 

  78. D.M. Cole, P.M. Newman, 3D SLAM in outdoor environments, in Proceedings of IEEE International Conference on Robotics and Automation (Orlando, May 2006), pp. 1556–1563

    Google Scholar 

  79. C. Leung, S. Huang, N. Kwok, G. Dissanayake, Planning under uncertainty using model predictive control for information gathering. Robot. Auton. Syst. 54(11), 898–910 (2006)

    Article  Google Scholar 

  80. T. Vidal-Calleja, A. Sanfeliu, J. Andrade-Cetto, Action selection for single camera SLAM. IEEE Trans. Syst. Man, Cybern. B 40(6), 1567–1581, (2010). (Dec 2010)

    Google Scholar 

Download references

Author information

Authors and Affiliations

Authors

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 Back-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_3

Download citation

  • DOI: https://doi.org/10.1007/978-3-319-60603-3_3

  • 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