Qualitative Acceleration Model: Representation, Reasoning and Application

  • Ester Martinez-Martin
  • Maria Teresa Escrig
  • Angel P. del Pobil
Part of the Advances in Intelligent Systems and Computing book series (AISC, volume 217)

Abstract

On the way to autonomous service robots, spatial reasoning plays a main role since it properly deals with problems involving uncertainty. In particular, we are interested in knowing people’s pose to avoid collisions. With that aim, in this paper, we present a qualitative acceleration model for robotic applications including representation, reasoning and a practical application.

Preview

Unable to display preview. Download preview PDF.

Unable to display preview. Download preview PDF.

References

  1. 1.
    Cioaca, E., Linnebank, F., Bredeweg, B., Salles, P.: A qualitative reasoning model of algal bloom in the danube delta biosphere reserve (ddbr). Ecol. Informatics 4(5-6), 282–298 (2009)CrossRefGoogle Scholar
  2. 2.
    Clementini, E., Felice, P.D., Hernández, D.: Qualitative representation of positional information. AI 95(2), 317–356 (1997)MATHGoogle Scholar
  3. 3.
    Cohn, A., Hazarika, S.: Qualitative spatial representation and reasoning: An overview. Fundamenta Informaticae 46(1-2), 1–29 (2001)MATHMathSciNetGoogle Scholar
  4. 4.
    Escrig, M., Toledo, F.: Reasoning with compared distances at different levels of granularity. In: CAEPIA, Gijón, Spain (2001)Google Scholar
  5. 5.
    Freksa, C.: Using orientation information for qualitative spatial reasoning. In: Frank, A.U., Formentini, U., Campari, I. (eds.) GIS 1992. LNCS, vol. 639, pp. 162–178. Springer, Heidelberg (1992)CrossRefGoogle Scholar
  6. 6.
    King, R., Garrett, S., Coghill, G.: On the use of qualitative reasoning to simulate and identify metabolic pathways. Bioinformatics 21(9), 2017–2026 (2005)CrossRefGoogle Scholar
  7. 7.
    Knauff, M., Strube, G., Jola, C., Rauh, R., Schlieder, C.: The psychological validity of qualitative spatial reasoning in one dimension. Spatial Cognition & Computation 4(2), 167–188 (2004)CrossRefGoogle Scholar
  8. 8.
    Levinson, S.: Space in Language and Cognition. Explorations in Cognitive Diversity. Cambridge University Press, UK (2003)CrossRefGoogle Scholar
  9. 9.
    Liu, H., Brown, D., Coghill, G.: Fuzzy qualitative robot kinematics. IEEE Trans. on Fuzzy Systems 16(3), 808–822 (2008)CrossRefGoogle Scholar
  10. 10.
    Martínez-Martín, E., Escrig, M.T., del Pobil, A.P.: A General Framework for Naming Qualitative Models Based on Intervals. In: Omatu, S., Paz Santana, J.F., González, S.R., Molina, J.M., Bernardos, A.M., Rodríguez, J.M.C. (eds.) Distributed Computing and Artificial Intelligence. AISC, vol. 151, pp. 681–688. Springer, Heidelberg (2012)CrossRefGoogle Scholar
  11. 11.
    Renz, J., Nebel, B.: Qualitative Spatial Reasoning Using Constraint Calculi, pp. 161–215. Springer, Berlin (2007)Google Scholar
  12. 12.
    van de Weghe, N., Cohn, A., de Tré, G., de Maeyer, P.: A qualitative trajectory calculus as a basis for representing moving objects in geographical information systems. Control and Cybernetics 35(1), 97–119 (2006)MATHGoogle Scholar
  13. 13.
    Westphal, M., Wölfl, S.: Qualitative csp, finite csp, and sat: Comparing methods for qualitative constraint-based reasoning. In: IJCAI, pp. 628–633 (2009)Google Scholar
  14. 14.
    Zadeh, L.: A new direction in ai. toward a computational theory of perceptions. AI Magazine 22(1), 73–84 (2001)Google Scholar

Copyright information

© Springer International Publishing Switzerland 2013

Authors and Affiliations

  • Ester Martinez-Martin
    • 1
  • Maria Teresa Escrig
    • 2
  • Angel P. del Pobil
    • 1
  1. 1.Universitat Jaume-ICastellónSpain
  2. 2.Cognitive Robot, S.L. Parque Científico, Tecnológico y Empresarial (ESPAITEC)Universitat Jaume-ICastellónSpain

Personalised recommendations