Skip to main content
SpringerLink
Log in
Book cover

Probabilistic Reasoning and Decision Making in Sensory-Motor Systems pp 99–127Cite as

Topological SLAM

  • Chapter

Part of the book series: Springer Tracts in Advanced Robotics ((STAR,volume 46))

Introduction

In all our daily activities, the natural surroundings that we inhabit play a crucial role. Many neurophysiologists have dedicated their efforts towards understanding how our brains can create internal representations of physical space. Both neurobiologists and roboticists are interested in understanding the behaviour of intelligent beings like us and their capacity to learn and use their knowledge of the spatial representation to navigate. The ability of intelligent beings to localize themselves and to find their way back home is linked to their internal “mapping system”. Most navigation approaches require learning and consequently entail memorizing information. Stored information can be organized into cognitive maps - a term introduced for the first time in (Tolman, 1948). Tolman advocates that the animals (rats) do not learn space as a sequence of movements; instead, the animal’s spatial capabilities rest on the construction of maps, which represent the spatial relationships between features in the environment

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   129.00
Price excludes VAT (USA)
  • Available as 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
Hardcover Book
USD   169.99
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

Preview

Unable to display preview. Download preview PDF.

Unable to display preview. Download preview PDF.

References

  • Aho, A.V.: Algorithms for finding patterns in strings, pp. 254–300. Elsevier Science Publishers B. V (1990)

    Google Scholar 

  • Arleo, A., Gerstner, W.: Spatial cognition and neuro-mimetic navigation: a model of hippocampal place cell activity. Biological Cybernetics 83, 287–299 (2000)

    Article  Google Scholar 

  • Baeza-Yates, R., Navarro, G.: Faster approximate string matching. Algorithmica 23(2), 127–158 (1999)

    Article  MATH  MathSciNet  Google Scholar 

  • Battaglia, F.P., Sutherland, G.R., McNaughton, B.L.: Local sensory cues and place cell directionality: additional evidence of prospective coding in the hippocampus. Journal of Neuroscience 24, 4541–4550 (2004)

    Article  Google Scholar 

  • Beeson, P., Jong, K.N., Kuipers, B.: Towards autonomous topological place detection using the extended voronoi graph. In: IEEE International Conference on Robotics and Automaton (ICRA), Barcelona, Spain, pp. 4373–4379 (2005)

    Google Scholar 

  • Bilmes, J.: A gentle tutorial on the em algorithm and its application to parameter estimation for gaussian mixture and hidden markov models (1997), citeseer.ist.psu.edu/bilmes98gentle.html

  • Cassandra, R., Kaelbling, A.L.P., Kurien, A.J.: Acting under uncertainty: Discrete bayesian models for mobile-robot navigation. In: IEEE/RSJ International Conference on Intelligent Robots and Systems (IROS), Osaka, Japan, vol. 2, pp. 963–972 (1996)

    Google Scholar 

  • Castellanos, J.A., Tardos, J.D.: Mobile Robot Localization and Map Building: Multisensor Fusion Approach. Kluwer Academic Publishers, Dordrecht (1999)

    Google Scholar 

  • Cho, Y.H., Giese, K.P., Tanila, H.T., Silva, A.J., Eichenbaum, H.: Abnormal hippocampal spatial representations in alphaCaMKIIT286A and CREBalphaDelta- mice. Science 279, 867–869 (1998)

    Article  Google Scholar 

  • Choset, H., Nagatani, K.: Topological simultaneous localization and mapping (SLAM): Toward exact localization without explicit localization. IEEE Transactions On Robotics and Automation 17(2), 125–137 (2001)

    Article  Google Scholar 

  • Cressant, A., Muller, R.U., Poucet, B.: Remapping of place cells firing patterns after maze rotations. Journal on Experiences on Brain Research 143, 470–479 (2002)

    Article  Google Scholar 

  • Dissanayake, M., Newman, M.P., Clark, S., Durrant-Whyte, H., Csorba, M.: A solution to the simultaneous localization and map building (SLAM) problem. IEEE Transactions on Robotics and Automation 17(3), 229–241 (2001)

    Article  Google Scholar 

  • Douglas, D., Peucker, T.: Algorithms for the reduction of the number of points required to represent a digitized line or its caricature. The Canadian Cartographer 10(2), 112–122 (1973)

    Google Scholar 

  • Dufourd, D., Chatila, R., Luzeaux, D.: Combinatorial maps for simultaneous localization and map buiding (SLAM). In: IEEE/RSJ International Conference on Intelligent Robots and Systems (IROS), vol. 2, pp. 1047–1052 (2004)

    Google Scholar 

  • Gallistel, R.: The Organization of Learning. MIT Press, Cambridge (1990)

    Google Scholar 

  • Gothard, K.M., Skaggs, W.E., Moore, K.M., McNaughton, B.L.: Binding of hippocampal ca1 neural activity to multiple reference frames in a landmark-based navigation task. Journal of Neuroscience 16, 823–835 (1996)

    Google Scholar 

  • Hafner, V.V.: Learning places in newly explored environments. In: Publication of the International Society for Adaptive Behavior, Honolulu, USA (2000)

    Google Scholar 

  • Hartley, T., Burgess, N., Lever, C., Cacucci, F., O’Keefe, J.: Modeling place fields in terms of the cortical inputs to the hippocampus. Hippocampus 10, 369–379 (2000)

    Article  Google Scholar 

  • Kali, S., Dayan, P.: The involvement of recurrent connections in area ca3 in establishing the properties of place fields: a model. Hippocampus 20, 7463–7477 (2000)

    Google Scholar 

  • Kanade, T., Ohta, Y.: Stereo by intra- and inter-scanline search using dynamic programming. IEEE Transactions on Pattern Analysis and Machine Intelligence (PALMZ) 3 (1985)

    Google Scholar 

  • Kortenkamp, D., Weymouth, T.: Topological mapping for mobile robots using a combination of sonar and vision sensing. In: American Association for Artificial Intelligence (AAAI), Seattle, WA, USA (1994)

    Google Scholar 

  • Kuipers, B.J.: Modeling spatial knowledge. Cognitive Science 2, 129–153 (1978)

    Article  Google Scholar 

  • Lamon, P., Nourbakhsh, I., Jensen, B., Siegwart, R.: Deriving and matching image fingerprint sequences for mobile robot localization. In: IEEE International Conference on Robotics and Automation (ICRA), Seoul, Korea, vol. 2, pp. 1609–1614 (2001)

    Google Scholar 

  • Lamon, P., Tapus, A., Glauser, E., Tomatis, N., Siegwart, R.: Environmental modeling with fingerprint sequences for topological global localization. In: IEEE/RSJ International Conference on Intelligent Robots and Systems (IROS), Las Vegas, USA, vol. 4, pp. 3781–3786 (2003)

    Google Scholar 

  • Leonard, J.J., Durrant-Whyte, H.F.: Directed Sonar Sensing for Mobile Robot Navigation. Kluwer Academic Publisher, Dordrecht (1992)

    MATH  Google Scholar 

  • Lisien, B., Morales, D., Silver, G., Kantor, D., Rekleitis, I., Choset, H.: Hierarchical simultaneous localization and mapping. In: IEEE/RSJ International Conference on Intelligent Robots and Systems (IROS), Las Vegas, USA, vol. 1, pp. 448–453 (2003)

    Google Scholar 

  • Martinelli, A., Tapus, A., Arras, K.O., Siegwart, R.: Multi-resolution slam for real world navigation. In: The 11th International Symposium of Robotics Research (ISRR), Siena, Italy (2003)

    Google Scholar 

  • Moutarlier, P., Chatila, R.: Stochastic multisensory data fusion for mobile robot location and environment modeling. In: The 5th International Symposium on Robotics Research (ISRR), Tokyo, Japan (1989)

    Google Scholar 

  • Needleman, S., Wunsch, C.: A general method applicable to the search for similarities in the amino acid sequence of two proteins. Journal on Molecular Biology 48, 443–453 (1970)

    Article  Google Scholar 

  • O’Keefe, J., Dostrovsky, J.: The hippocampus as a spatial map. preliminary evidence from unit activity in the freely-moving rat. Journal of Brain Research 34, 171–175 (1971)

    Article  Google Scholar 

  • O’Keefe, J., Nadel, L.: The hippocampus as a cognitive map, Clarendon, Oxford (1978)

    Google Scholar 

  • Owen, C., Nehmzow, U.: Landmark-based navigation for a mobile robot. In: From Animals to Animats: Fifth International Conference on Simulation of Adaptive Behavior (SAB), pp. 240–245. MIT Press, Cambridge (1998)

    Google Scholar 

  • Redish, D.A.: Beyond the Cognitive Map: From Place Cells to Episodic Memory. MIT Press, Cambridge (1999)

    Google Scholar 

  • Se, S., Lowe, D., Little, J.: Mobile robot localization and mapping with uncertainty using scale-invariant visual landmarks. International Journal of Robotics Research (IJRR) 21(8), 735–758 (2002)

    Article  Google Scholar 

  • Skaggs, E.W., McNaughton, L.B.: Spatial firing properties of hippocampal ca1 populations in an environment containing two visually identical regions. Journal of Neuroscience 18, 8455–8466 (1998)

    Google Scholar 

  • Smith, C.R., Cheeseman, P.: On the representation and estimation of spatial uncertainty. International Journal of Robotics Research 5(4), 56–68 (1986)

    Article  Google Scholar 

  • Tapus, A.: Topological SLAM - Simultaneous Localization and Mapping with Fingerprints of Places. Ph.d thesis, Ecole Politechnique Federale de Lausanne (EPFL), Lausanne, Switzerland (2005)

    Google Scholar 

  • Tapus, A., Siegwart, R.: Incremental robot mapping with fingerprints of places. In: IEEE/RSJ International Conference on Intelligent Robots and Systems (IROS), Edmonton, Canada, pp. 2429–2434 (2005)

    Google Scholar 

  • Tapus, A., Tomatis, N., Siegwart, R.: Topological global localization and mapping with fingerprint and uncertainty. In: The 9th International Symposium on Experimental Robotics (ISER), Singapore, pp. 99–111 (2004)

    Google Scholar 

  • Thrun, S.: Probabilistic algorithms in robotics. Artificial Intelligence Magazine 21, 93–109 (2000)

    Google Scholar 

  • Thrun, S.: Learning metric-topological maps for indoor mobile robot navigation. Artificial Intelligence 99(1), 21–71 (1998)

    Article  MATH  Google Scholar 

  • Tolman, C.E.: Cognitive maps in rats and men. Psychological Review 55, 189–208 (1948)

    Article  Google Scholar 

  • Tomatis, N., Nourbakhsh, I., Siegwart, R.: Hybrid simultaneous localization and map building: a natural integration of topological and metric. Robotics and Autonomous Systems 44, 3–14 (2003)

    Article  Google Scholar 

Download references

Author information

Authors and Affiliations

  1. Interaction Lab, University of Southern California (USC),  

    Adriana Tapus

  2. Autonomous Systems Lab, Swiss Federal Institute of Technology Zürich (ETHZ),  

    Roland Siegwart

Authors
  1. Adriana Tapus
    View author publications

    You can also search for this author in PubMed Google Scholar

  2. Roland Siegwart
    View author publications

    You can also search for this author in PubMed Google Scholar

Editor information

Pierre Bessière Christian Laugier Roland Siegwart

Rights and permissions

Reprints and permissions

Copyright information

© 2008 Springer-Verlag Berlin Heidelberg

About this chapter

Cite this chapter

Tapus, A., Siegwart, R. (2008). Topological SLAM. In: Bessière, P., Laugier, C., Siegwart, R. (eds) Probabilistic Reasoning and Decision Making in Sensory-Motor Systems. Springer Tracts in Advanced Robotics, vol 46. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-540-79007-5_5

Download citation

  • DOI: https://doi.org/10.1007/978-3-540-79007-5_5

  • Publisher Name: Springer, Berlin, Heidelberg

  • Print ISBN: 978-3-540-79006-8

  • Online ISBN: 978-3-540-79007-5

  • eBook Packages: EngineeringEngineering (R0)

Publish with us

Policies and ethics

Search

Navigation