Skip to main content

Representation of 3D Space and Sensor Modelling Within a Probabilistic Framework

  • Chapter
Probabilistic Approaches to Robotic Perception

Part of the book series: Springer Tracts in Advanced Robotics ((STAR,volume 91))

  • 1892 Accesses

Abstract

For living organisms, perception can be defined as a set of cognitive processes, in the sense that it consists in the processing of sensorial data in order to generate essential information with the purpose of building a coherent and useful representation of the surrounding world. Perception has been paramount for living beings, its importance having propagated from supporting the original primal objective of survival up to the more recent evolutionary purpose of promoting social interaction.

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 84.99
Price excludes VAT (USA)
  • Available as PDF
  • Read on any device
  • Instant download
  • Own it forever
Softcover Book
USD 109.99
Price excludes VAT (USA)
  • Compact, lightweight edition
  • Dispatched in 3 to 5 business days
  • Free shipping worldwide - see info
Hardcover Book
USD 109.99
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

Preview

Unable to display preview. Download preview PDF.

Unable to display preview. Download preview PDF.

References

  1. Ferreira, J.F., Lobo, J., Bessiére, P., Castelo-Branco, M., Dias, J.: A Bayesian Framework for Active Artificial Perception. IEEE Transactions on Systems, Man, and Cybernetics, Part B: Cybernetics 43(2), 699–711 (2013), doi:10.1109/TSMCB.2012.2214477

    Google Scholar 

  2. Portugal, D., Rocha, R.P.: Topological Information from Grid Maps for Robot Navigation. In: Proceedings of the 4th International Conference on Agents and Artificial Intelligence (ICAART 2012), Vilamoura, Portugal, pp. 137–143 (2012)

    Google Scholar 

  3. Ranganathan, A., Dellaer, F.: Online Probabilistic Topological Mapping. International Journal of Robotics Research 30(6), 755–771 (2011)

    Article  Google Scholar 

  4. Colas, F., Diard, J., Bessiére, P.: Common Bayesian Models For Common Cognitive Issues. Acta Biotheoretica 58(2-3), 191–216 (2010)

    Article  Google Scholar 

  5. Faria, D.R., Martins, R., Lobo, J., Dias, J.: Probabilistic Representation of 3D Object Shape by In-Hand Exploration. In: Proceedings of The 2010 IEEE/RSJ International Conference on Intelligent Robots and Systems, IROS 2010, Taipei, Taiwan (2010)

    Google Scholar 

  6. Wurm, K.M., Hornung, A., Bennewitz, M., Stachniss, C., Burgard, W.: OctoMap: A Probabilistic, Flexible, and Compact 3D Map Representation for Robotic Systems. In: Proceedings of the ICRA 2010 Workshop on Best Practice in 3D Perception and Modeling for Mobile Manipulation (2010)

    Google Scholar 

  7. Ferreira, J.F., Pinho, C., Dias, J.: Implementation and Calibration of a Bayesian Binaural System for 3D Localisation. In: 2008 IEEE International Conference on Robotics and Biomimetics (ROBIO 2008), Bangkok, Thailand (2009)

    Google Scholar 

  8. Burgess, N.: Spatial Cognition and the Brain. Annals of the New York Academy of Sciences 1124, 77–97 (2008)

    Article  Google Scholar 

  9. Byrne, P., Becker, S.: A principle for learning egocentric-allocentric transformation. Neural Computation 20(3), 709–737 (2008)

    Article  MATH  Google Scholar 

  10. Ferreira, J.F., Bessiére, P., Mekhnacha, K., Lobo, J., Dias, J., Laugier, C.: Bayesian Models for Multimodal Perception of 3D Structure and Motion. In: International Conference on Cognitive Systems (CogSys 2008), pp. 103–108. University of Karlsruhe, Karlsruhe (2008)

    Google Scholar 

  11. Wiener, J.M., Meilinger, T., Berthoz, A.: The integration of spatial information across different perspectives. In: Proceedings of the 30th Annual Conference of the Cognitive Science Society (CogSci 2008), pp. 2031–2036 (2008)

    Google Scholar 

  12. Doya, K., Ishii, S., Pouget, A., Rao, R.P.N. (eds.): Bayesian Brain — Probabilistic Approaches to Neural Coding. MIT Press (2007) ISBN 978-0-262-04238-3

    Google Scholar 

  13. Meilinger, T., Riecke, B.E., Bülthoff, H.H.: Orientation Specificity in Long-Term-Memory for Environmental Spaces. In: Proceedings of the 29th Annual Conference of the Cognitive Science Society (CogSci 2007), pp. 479–484 (2007)

    Google Scholar 

  14. Tapus, A., Battaglia, F., Siegwart, R.: The Hippocampal Place Cells and Fingerprints of Places: Spatial Representation Animals, Animats and Robots. In: Proceedings of the 9th International Conference on Intelligent Autonomous Systems, IAS-9 (2006)

    Google Scholar 

  15. Vasudevan, S., Nguyen, V., Siegwart, R.: Towards a Cognitive Probabilistic Representation of Space for Mobile Robots. In: Proceedings of the IEEE International Coference on Information Acquisition (ICIA), Shandong, China (2006)

    Google Scholar 

  16. Taddeo, M., Floridi, L.: Solving the symbol grounding problem: a critical review of fifteen years of research. Journal of Experimental and Theoretical Artificial Intelligence 17(4), 419–445 (2005)

    Article  Google Scholar 

  17. Faller, C., Merimaa, J.: Source localization in complex listening situations: Selection of binaural cues based on interaural coherence. Journal of the Acoustical Society of America 116(5), 3075–3089 (2004), doi:10.1121/1.1791872

    Article  Google Scholar 

  18. Kapralos, B., Jenkin, M.R.M., Milios, E.: Auditory Perception and Spatial (3D) Auditory Systems. Technical Report CS-2003-07, York University (2003)

    Google Scholar 

  19. Tomatis, N., Nourbakhsh, I., Siegwart, R.: Hybrid simultaneous localization and map building: a natural integration of topological and metric. Robotics and Autonomous Systems 44(1), 3–14 (2003)

    Article  Google Scholar 

  20. Cohen, Y.E., Anderson, R.E.: A Common Reference Frame for Movement Plans in the Posterior Parietal Cortex. Nature Reviews Neuroscience 3, 553–562 (2002)

    Article  Google Scholar 

  21. Gallistel, C.R.: Language and spatial frames of reference in mind and brain. TRENDS in Cognitive Sciences 6(8), 321–322 (2002)

    Article  Google Scholar 

  22. King, A.J., Schnupp, J.W., Doubell, T.P.: The shape of ears to come: dynamic coding of auditory space. TRENDS in Cognitive Sciences 5(6), 261–270 (2001)

    Article  Google Scholar 

  23. Shinn-Cunningham, B.G., Santarelli, S., Kopco, N.: Tori of confusion: Binaural localization cues for sources within reach of a listener. Journal of the Acoustical Society of America 107(3), 1627–1636 (2000)

    Article  Google Scholar 

  24. Colby, C.L.: Action-Oriented Spatial Reference Frames in Cortex. Neuron 20, 15–24 (1998) Review

    Article  Google Scholar 

  25. Klatzky, R.L.: Allocentric and egocentric spatial representations: Definitions, distinctions, and interconnections. In: Freksa, C., Habel, C., Wender, K.F. (eds.) Spatial Cognition 1998. LNCS (LNAI), vol. 1404, p. 1. Springer, Heidelberg (1998)

    Chapter  Google Scholar 

  26. McIntyre, J., Stratta, F., Lacquaniti, F.: Short-Term Memory for Reaching to Visual Targets: Psychophysical Evidence for Body-Centered Reference Frames. Journal of Neuroscience 18(20), 8423–8435 (1998)

    Google Scholar 

  27. Murphy, K.J., Carey, D.P., Goodale, M.A.: The Perception of Spatial Relations in a Patient with Visual Form Agnosia. Cognitive Neuropsyshology 15(6/7/8), 705–722 (1998)

    Article  Google Scholar 

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

    Article  MATH  Google Scholar 

  29. Cutting, J.E., Vishton, P.M.: Perceiving layout and knowing distances: The integration, relative potency, and contextual use of different information about depth. In: Epstein, W., Rogers, S. (eds.) Handbook of Perception and Cognition, vol. 5, Academic Press (1995) Perception of space and motion

    Google Scholar 

  30. Gordon, J., Ghilardi, M.F., Ghez, C.: Accuracy of planar reaching movements. I. Independence of direction and extent variability. Experimental Brain Research 99(1), 97–111 (1994)

    Article  Google Scholar 

  31. Kuipers, B., Byun, Y.T.: A robot exploration and mapping strategy based on a semantic hierarchy of spatial representations. Robotics and Autonomous Systems 8, 47–63 (1991)

    Article  Google Scholar 

  32. Leonard, J.J., Durrant-Whyte, H.F.: Mobile Robot Localization by Tracking Geometric Beacons. IEEE Transactions on Robotics and Automation 7(3), 376–382 (1991)

    Article  Google Scholar 

  33. Viemeister, N.F., Wakefield, G.H.: Temporal integration and multiple looks. The Journal of the Acoustical Society of America 90(2), 858–865 (1991)

    Article  Google Scholar 

  34. Gallistel, C.R.: The organization of learning. Learning, development, and conceptual change. MIT Press, Cambridge (1990)

    Google Scholar 

  35. Harnad, S.: The symbol grounding problem. Physica D 42, 335–346 (1990)

    Article  Google Scholar 

  36. Elfes, A.: Using occupancy grids for mobile robot perception and navigation. IEEE Computer 22(6), 46–57 (1989)

    Article  Google Scholar 

  37. Oppenheim, A.V., Schafer, R.: Discrete-Time Signal Processing (1989)

    Google Scholar 

  38. Moravec, H.P.: Sensor fusion in certainty grids for mobile robots. AI Magazine 9(2), 61–74 (1988)

    Google Scholar 

  39. Zurek, P.M.: The precedence effect. In: Yost, W., Gourevitch, G. (eds.) Directional Hearing. Springer (1987)

    Google Scholar 

  40. Moravec, H., Elfes, A.: High resolution maps from wide angle sonar. In: IEEE International Conference on Robotics and Automation (1985)

    Google Scholar 

Download references

Author information

Authors and Affiliations

Authors

Corresponding author

Correspondence to João Filipe Ferreira .

Rights and permissions

Reprints and permissions

Copyright information

© 2014 Springer International Publishing Switzerland

About this chapter

Cite this chapter

Ferreira, J.F., Dias, J. (2014). Representation of 3D Space and Sensor Modelling Within a Probabilistic Framework. In: Probabilistic Approaches to Robotic Perception. Springer Tracts in Advanced Robotics, vol 91. Springer, Cham. https://doi.org/10.1007/978-3-319-02006-8_2

Download citation

  • DOI: https://doi.org/10.1007/978-3-319-02006-8_2

  • Publisher Name: Springer, Cham

  • Print ISBN: 978-3-319-02005-1

  • Online ISBN: 978-3-319-02006-8

  • eBook Packages: EngineeringEngineering (R0)

Publish with us

Policies and ethics