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Topological modeling with Fuzzy Petri Nets for autonomous mobile robots

  • Javier de Lope
  • Dario Maravall
  • José G. Zato
2 Modification Tasks Perception Robotics
Part of the Lecture Notes in Computer Science book series (LNCS, volume 1416)

Abstract

In this paper a novel method of reference places' detection to build topological models is described, as well as an algorithm for route planning based on Fuzzy Petri Nets. The proposed method for the detection of reference places does not employ sensory information but the information provided by the robot's control subsystem. The reference places and the navigation strategies between places are used for constructing the model's environment with a Fuzzy Petri Net. The route planning algorithm propagates over the net the certainty value of places and transitions. After finishing the propagation the transitions and the places store the information needed to make decisions about the navigation strategies of the robot route.

Keywords

Mobile Robot Fuzzy Reasoning Route Planning Autonomous Mobile Robot Navigation Strategy 
These keywords were added by machine and not by the authors. This process is experimental and the keywords may be updated as the learning algorithm improves.

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References

  1. 1.
    Agre, P.E., Chapman, D.: What are plans for? In: P. Maes (ed.): Designing Autonomous Robots. MIT Press. Cambridge. Massachusetts (1991) 17–34Google Scholar
  2. 2.
    Chen, S.M., Ke, J.S., Chang, J.F.: Knowledge representation using Fuzzy Petri Nets. IEEE Trans. on Knowledge and Data Engineering 2(3) (1990) 311–319Google Scholar
  3. 3.
    Cox, I.J.: Blanche — An experiment in guidance and navigation of an autonomous robot vehicle. IEEE Trans. on Robotics and Automation. 7(2) (1991) 193–204Google Scholar
  4. 4.
    Kuipers. B.J.. Byun. Y.T.: A robust; qualitative approach to a spatial learning mobile robot. In SPIE Vol. 1003 Sensor Fusion: Spatial Reasoning and Science Interpretation (1988) 366–375Google Scholar
  5. 5.
    Kuipers, B.J., Byun, Y.T.: A robot exploration and mapping strategy based on a semantic hierarchy of spatial representations. In W. van de Velde. (ed.): Toward Learning Robots. MIT Press. Cambridge. Massachusetts (1993) 47–63Google Scholar
  6. 6.
    Kurz, A.: Constructing maps for mobile robot navigation based on ultrasonic range data. IEEE Trans. on Systems. Man and Cybernetics-Part B: Cybernetics. 26(2) (1996) 233–242Google Scholar
  7. 7.
    Looney, C.L.: Fuzzy Petri Nets for rule-based decisionmaking. IEEE Trans. on Systems, Man, and Cybernetics. 18(1) (1988) 178–183Google Scholar
  8. 8.
    Matarić, M.J.: Integration of representation into goal-driven behavior-based robots. IEEE Trans. on Robotics and Automation. 8(3) (1992) 304–312Google Scholar
  9. 9.
    Moravec, H.P.. Elfes. A.: High resolution maps from wide angle sonar. In Proc. of IEEE Int. Conf. on Robotics and Automation (1985) 116–121Google Scholar
  10. 10.
    Murata, T.: Petri Nets: Properties, analysis and applications. Proc. of the IEEE 77(4) (1989) 541–580Google Scholar
  11. 11.
    Nehmzow. U.. Smithers. T.: Using motor actions for location recognition. In Proc. of the First European Conf. on Artificial Life (1991) 96–104Google Scholar
  12. 12.
    Payton, D.W.: Internalized Plans: A representation for action resources. In: P. Maes (ed.): Designing Autonomous Robots. MIT Press. Cambridge. Massachusetts (1991) 89–103Google Scholar
  13. 13.
    Serradilla. F.: Arquitectura cognitiva basada en el gradiente sensorial y su aplicación a la Robótica Móvil. Ph.D. Dissertation. Dept. Artificial Intelligence. Technical University of Madrid (1997)Google Scholar
  14. 14.
    Yu, S.K.: Comments on “Knowledge representation using Fuzzy Petri Nets”. IEEE Trans. on Knowledge and Data Engineering 7(1) (1995) 190–191Google Scholar

Copyright information

© Springer-Verlag Berlin Heidelberg 1998

Authors and Affiliations

  • Javier de Lope
    • 1
  • Dario Maravall
    • 2
  • José G. Zato
    • 1
  1. 1.Dept. Applied Intelligent SystemsTechnical University of MadridSpain
  2. 2.Dept. Artificial IntelligenceTechnical University of MadridSpain

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