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Segmentation of behavioral spaces for navigation tasks

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Abstract

From the very beginning, the forefathers of the Artificial Intelligence field (McCarthy, Minsky, Newel and Simon) have emphasized the importance of the internal representation of an agent, whether artificial or biological. The issue that has been debated for the last 30 years is what the exact form of this representation is. In fact some philosophers, such as Dreyfus [5], even doubt whether this internal representation can ever be formalized. In this paper we shall assume such a formalism exists and do our part to address the long-debated question of what it is or what it should be.

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References

  1. Arbib, M.A.: The Metaphorical Brain. New York: Wily-Interscience 1972.

    MATH  Google Scholar 

  2. Ashby, W.R.: Design for a Brain. London: Chapman & Hall and Science Paperbacks 1952.

    Google Scholar 

  3. Brockett, R.: Hybrid Models for Motion Control Systems. In: Trentelman, H.L. and Willens, J.C. (eds.): Essays on Control: Perspectives in the Theory and its Applications. Boston: Birkhauser 1993.

    Google Scholar 

  4. Brooks, R.: Intelligence without Representation. Artificial Intelligence, 47 (13) (January 1991).

    Google Scholar 

  5. Dreyfus, H.L.: What Computers Can’t Do: A Critique of Artificial Reason. New York: Harper & Row 1972.

    Google Scholar 

  6. Khatib, O.: Real-time Obstacle Avoidance for Manipulators and Mobile Robots. International Journal of Robotics Research, 5 (1), 90–98 (1986).

    Article  MathSciNet  Google Scholar 

  7. Koditschek, D.: Robot Planning and Control via Potential Functions. Robotics Review (1992).

    Google Scholar 

  8. Kollnig, H., Nagel, H.-H., Otte, M.: Association of Motion Verbs with Vehicle Movements Extracted from Dense Optical Flow Fields. In: Eklundh, J.-O. (ed.): Proc. 3rd European Conf. on Computer Vision, Vol. II. Berlin Heidelberg New York: Springer-Verlag 1994 (Lecture Notes in Computer Science, vol. 801, pp. 338–347 )

    Google Scholar 

  9. Košecká,, J.: A Framework for Modeling and Verifying Visually-Guided Agents: Design, Analysis and Experiments. Ph.D. thesis, Computer & Information Science Dept., University of Pennsylvania, Philadelphia, PA, 1996.

    Google Scholar 

  10. Latombe, J.C.: Robot Motion Planning. Boston: Kluwer Academic 1991.

    Book  Google Scholar 

  11. Lozano-Perez, T.: Spatial Planning: A Configuration Space Approach. IEEE Transactions on Computers, C-32, 2 (February 1983).

    Google Scholar 

  12. McCarthy, J.: Programs with Common Sense. In: Proceedings of the Teddington Conference on the Mechanization of Thought Processes. London: Her Majesty’s Stationary Office 1959.

    Google Scholar 

  13. McCarthy, J.: Generality in Artificial Intelligence. Communications of the ACM, 30 (12) 1030–1035 (1987).

    Article  MathSciNet  MATH  Google Scholar 

  14. Minsky, M.: A Framework for Representing Knowledge. In: Winston P.H. (ed.): The Psychology of Computer Vision. New York: McGraw-Hill 1975.

    Google Scholar 

  15. Murray, M., Li, Z., Sastry, S.S.: A Mathematical Introduction to Robotic Manipulation. Boca Raton, FL: CRC Press 1994.

    Google Scholar 

  16. Newell, A., Simon, H.A.: Computer Science as Empirical Inquiry and Search. Communications of the ACM, 19 (3), 113–126 (1976).

    Article  MathSciNet  Google Scholar 

  17. Ramadge, P.J., Wonham, W.M.: The Control of Discrete Event Systems. Proceedings of the IEEE, 77 (1), 81–97 (January 1989).

    Article  Google Scholar 

  18. ] Schöner, G., Dose, M.: A Dynamical System Approach to Task-level System Integration Used to Plan and Control Autonomous Vehicle Motion. Robotics and Autonomous Systems, 10, 253–267 (1992).

    Article  Google Scholar 

  19. Schwartz, J.T., Sharir M., Hoperoft, J. (eds.): Planning, Geometry and Complexity of Robot Motion. Norwood, NJ: Ablex Publishing 1987.

    Google Scholar 

  20. Smolensky, P.: On the Proper Treatment of Connectionism. Behavioral and Brain Sciences, 11, 1–74 (1988).

    Article  Google Scholar 

  21. Taylor, C.J., Kriegman, D.J.: Vision-Based Motion Planning and Exploration Algorithms for Mobile Robots. Proceedings of the Workshop on the Algorithmic Foundations of Robotics, 1994.

    Google Scholar 

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© 1997 Springer-Verlag/Wien

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Bajcsy, R., Christensen, H.I., Košecká, J. (1997). Segmentation of behavioral spaces for navigation tasks. In: Solina, F., Kropatsch, W.G., Klette, R., Bajcsy, R. (eds) Advances in Computer Vision. Advances in Computing Science. Springer, Vienna. https://doi.org/10.1007/978-3-7091-6867-7_25

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  • DOI: https://doi.org/10.1007/978-3-7091-6867-7_25

  • Publisher Name: Springer, Vienna

  • Print ISBN: 978-3-211-83022-2

  • Online ISBN: 978-3-7091-6867-7

  • eBook Packages: Springer Book Archive

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