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Geometrical Representation of Quantity Space and Its Application to Robot Motion Description

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Book cover Knowledge-Based Intelligent Information and Engineering Systems (KES 2007)

Part of the book series: Lecture Notes in Computer Science ((LNAI,volume 4693))

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Abstract

We are interested in the problem of intelligent connection of perception to action, i.e., the connection between numerical data and cognitive functions. In this paper we extend conventional quantity space into that in a geometric vector context and then propose quantity arithmetic for quantity vector computation in a normalized quantity space. An example of motion abstraction of a Puma robot is provided to demonstrate the effectiveness of the proposed method.

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References

  1. Brady, M.: Artificial intelligence and robotics. Artificial intelligence 26, 79–121 (1985)

    Article  Google Scholar 

  2. Coradeschi, S., Saffiotti, A.: Journal of robotics and autonomous systems, special issue on perceptual anchoring (2003)

    Google Scholar 

  3. Forbus, K.: Qualitative process theory. Artificial Intelligence 24, 85–168 (1984)

    Article  Google Scholar 

  4. Kuipers, B.: Qualitative reasoning. MIT Press, Cambridge (1994)

    Google Scholar 

  5. Coghill, G.M.: Mycroft: A Framework for Constraint-Based Fuzzy Qualitative Reasoning. PhD thesis, Heriot-Watt University (1996)

    Google Scholar 

  6. Shen, Q., Leitch, R.: Fuzzy qualitative simulation. IEEE Transactions on Systems, Man, and Cybernetics 23(4), 1038–1061 (1993)

    Article  Google Scholar 

  7. Ali, A., Dubois, D., Prade, H.: Qualitative reasoning based on fuzzy relative orders of magnitude. IEEE transactions on Fuzzy Systems 11(1), 9–23 (2003)

    Article  Google Scholar 

  8. Neumaier, A.: Interval methods for systems of equations. In: Encyclopedia of mathematics and its applications, Cambridge University Press, Cambridge (1990)

    Google Scholar 

  9. Rump, S.: Fast and parallel interval arithmetic. BIT 39(3), 534–554 (1999)

    Article  MathSciNet  MATH  Google Scholar 

  10. Ohlbach, H., Koehler, J.: Modal logics, description logics adn arithmetic. Artificial Intelligence 109(1-2), 1–31 (1999)

    Article  MathSciNet  MATH  Google Scholar 

  11. Yager, R., Rybalob, A.: Full reinforcement operators in aggregation techniques. IEEE Transactions on Systems, Man and Cybernetics 28, 757–769 (1998)

    Article  Google Scholar 

  12. Carlsson, C., Fuller, R.: On possibilistic mean value and variance of fuzzy numbers. Fuzzy Sets and Systems 122, 315–326 (2001)

    Article  MathSciNet  MATH  Google Scholar 

  13. Liu, H., Brown, D.: An extension to fuzzy qualitative trigonometry and its application to robot kinematics. In: Proc. IEEE International Conference on Fuzzy Systems, Canada, pp. 1111–1118 (2006)

    Google Scholar 

  14. Liu, H., Coghill, G.: Fuzzy qualitative trigonometry. In: Proc. IEEE International Conference on Systems, Man and Cybernetics, Hawaii, USA (2005)

    Google Scholar 

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Author information

Authors and Affiliations

  1. Institute of Industrial Research, The University of Portsmouth, Portsmouth PO1 3HE, England, UK

    Honghai Liu & David J. Brown

  2. Department of Computing Science, The University of Aberdeen, Aberdeen, AB24 3UE, Scotland, UK

    George M. Coghill

Authors
  1. Honghai Liu
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  2. David J. Brown
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  3. George M. Coghill
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Editor information

Editors and Affiliations

  1. Dipartimento di Scienze dell’Informazione, Università degli Studi di Milano, Via Comelico 39/41, 20135, Milano, Italy

    Bruno Apolloni

  2. Centre for SMART Systems, School of Engineering, University of Brighton, BN2 4GJ, Brighton, UK

    Robert J. Howlett

  3. Knowledge-Based Intelligent Engineering Systems Centre, University of South Australia, Mawson Lakes, SA 5095, Adelaide, Australia

    Lakhmi Jain

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© 2007 Springer-Verlag Berlin Heidelberg

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Liu, H., Brown, D.J., Coghill, G.M. (2007). Geometrical Representation of Quantity Space and Its Application to Robot Motion Description. In: Apolloni, B., Howlett, R.J., Jain, L. (eds) Knowledge-Based Intelligent Information and Engineering Systems. KES 2007. Lecture Notes in Computer Science(), vol 4693. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-540-74827-4_3

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  • DOI: https://doi.org/10.1007/978-3-540-74827-4_3

  • Publisher Name: Springer, Berlin, Heidelberg

  • Print ISBN: 978-3-540-74826-7

  • Online ISBN: 978-3-540-74827-4

  • eBook Packages: Computer ScienceComputer Science (R0)

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