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Exploration: Simultaneous Localization and Mapping (SLAM)

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Computer Vision

Synonyms

Concurrent mapping and localization (CML); Visual SLAM

Related Concepts

Structure-from-Motion (SfM)

Definition

Exploration refers to gathering data about an environment through sensors in order to discover its structure. A fundamental technique for exploration of an unknown environment is Simultaneous Localization and Mapping (SLAM). SLAM is a technique that supports the incremental building of a 3-D map representation of an environment while also using the same incremental map to accurately localize the observer in order to minimize errors in the map building. SLAM techniques can be implemented with laser range finders, monocular vision, stereo vision, and RGB-D cameras.

Background

An accurate representation of an environment is highly useful for autonomous and human assistive applications. Such a representation can be a high level minimalistic map derived from a sparse set of landmarks or a detailed dense 3-D model (e.g., Fig. 1). An accurate map can be used to perform...

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References

  1. Henry P, Krainin M, Herbst E, Ren X, Fox D (2012) RGB-D mapping: using Kinect-style depth cameras for dense 3D modeling of indoor environments. Intern J Robot Res 31(5):647–663

    Article  Google Scholar 

  2. Hartley RI, Zisserman A (2004) Multiple view geometry in computer vision, 2nd edn. Cambridge University Press, Cambridge. ISBN: 0521540518

    Book  MATH  Google Scholar 

  3. Smith R, Self M, Cheeseman P (1990) Autonomous robot vehicles. In: Estimating uncertain spatial relationships in robotics. Springer, New York, pp 167–193

    Book  Google Scholar 

  4. Neira J, Tardos JD (2001) Data association in stochastic mapping using the joint compatibility test. IEEE Trans Robot Autom 17(6):890–897

    Article  Google Scholar 

  5. Chli M, Davison AJ (2008) Active matching. In: Proceedings of 10th European conference on computer vision (ECCV’08), Marseille

    Google Scholar 

  6. Williams B, Klein G, Reid I (2007) Real-time SLAM relocalisation. In: Proceedings of IEEE 11th international conference on computer vision ICCV 2007, Rio de Janeiro, pp 1–8

    Google Scholar 

  7. Durrant-Whyte H, Bailey T (2006) Simultaneous localization and mapping: part i. IEEE Robot Autom Mag 13(2):99–110

    Article  Google Scholar 

  8. Bailey T, Durrant-Whyte H (2006) Simultaneous localization and mapping (SLAM): part ii. IEEE Robot Autom Mag 13(3):108–117

    Article  Google Scholar 

  9. Thrun S, Burgard W, Fox D (2005) Probabilistic robotics. In: Intelligent robotics and autonomous agents. MIT, Cambridge

    MATH  Google Scholar 

  10. Montemerlo M, Thrun S, Koller D, Wegbreit B (2002) FastSLAM: a factored solution to the simultaneous localization and mapping problem. In: Proceedings of the AAAI national conference on artificial intelligence, Edmonton. AAAI, pp 593–598

    Google Scholar 

  11. Montemerlo M, Thrun S, Koller D, Wegbreit B (2003) FastSLAM 2.0: an improved particle filtering algorithm for simultaneous localization and mapping that provably converges. In: Proceeding of the international conference on artificial intelligence (IJCAI), Acapulco, pp 1151–1156

    Google Scholar 

  12. Civera J, Davison AJ, Montiel J (2008) Inverse depth parametrization for monocular SLAM. IEEE Trans Robot 24(5):932–945

    Article  Google Scholar 

  13. Marzorati D, Matteucci M, Migliore D, Sorrenti DG (2009) On the use of inverse scaling in monocular SLAM. In: Proceedings of IEEE international conference on robotics and automation ICRA’09, Kobe, pp 2030–2036

    Google Scholar 

  14. Strasdat H, Montiel JMM, Davison AJ (2010) Real-time monocular SLAM: why filter? In: Proceedings of IEEE international robotics and automation (ICRA) conference, Anchorage, pp 2657–2664

    Google Scholar 

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

    Article  Google Scholar 

  16. Williams B, Cummins M, Neira J, Newman P, Reid I, Tardos J (2008) An image-to-map loop closing method for monocular SLAM. In: Proceedings of IEEE/RSJ international conference on intelligent robots and systems IROS 2008, Nice, pp 2053–2059

    Google Scholar 

  17. Eade E, Drummond T (2008) Unified loop closing and recovery for real time monocular SLAM. In: BMVC 2008, Leeds

    Google Scholar 

  18. Castle RO, Klein G, Murray DW (2010) Combining monoSLAM with object recognition for scene augmentation using a wearable camera. J Image Vis Comput 28(11): 1548–1556

    Article  Google Scholar 

  19. Migliore D, Rigamonti R, Marzorati D, Matteucci M, Sorrenti DG (2009) Use a single camera for simultaneous localization and mapping with mobile object tracking in dynamic environments. In: Proceedings of international workshop on safe navigation in open and dynamic environments application to autonomous vehicles, Kobe

    Google Scholar 

  20. Davison AJ, Reid ID, Molton ND, Stasse O (2007) MonoSLAM: real-time single camera SLAM. IEEE Trans Pattern Anal Mach Intell 29(6):1052–1067

    Article  Google Scholar 

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Author information

Authors and Affiliations

  1. Canberra Research Laboratory, NICTA, Canberra, Australia

    Samunda Perera

  2. Australian National University, 0200, Canberra, Australia

    Dr.Nick Barnes

  3. CSIRO, Information Sciences, Canberra, Australia

    Dr.Alexander Zelinsky

Authors
  1. Samunda Perera
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  2. Dr.Nick Barnes
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  3. Dr.Alexander Zelinsky
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Corresponding author

Correspondence to Samunda Perera .

Editor information

Editors and Affiliations

  1. Institute of Industrial Science, The University of Tokyo, Tokyo, Japan

    Katsushi Ikeuchi

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© 2014 Springer Science+Business Media New York

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Perera, S., Barnes, D., Zelinsky, D. (2014). Exploration: Simultaneous Localization and Mapping (SLAM). In: Ikeuchi, K. (eds) Computer Vision. Springer, Boston, MA. https://doi.org/10.1007/978-0-387-31439-6_280

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