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A framework for intelligent control

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Abstract

Blackboard architecture is a flexible and powerful expert system framework. It represents an approach to problem-solving that is useful in many domains of applications, especially in the area of intelligent control. Blackboard architecture can provide an environment for achieving intelligent control behaviour in many AI systems. In this paper, a brief description of blackboard architecture is given. The potential and usefulness of this structured framework is examined. The discussions on the application of blackboard architecture is in the domain of real-time control of an autonomous mobile robot in a hazardous material spill emergency situation.

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References

  1. Meystel, A., Intelligent control: highlights and shadows, Proc. IEEE International Symp. on Intelligent Control, Philadelphia, pp. 2–8 (1987).

  2. Hayes-Roth, B., A Blackboard architecture for control, Artificial Intelligence 26, 251–321 (1985).

    Google Scholar 

  3. Nii, H.P., Blackboard systems: The blackboard model of problem solving and the evolution of blackboard architecture, The AI Magazine, Part I, 38–53, Summer (1986). Part II, 82–106, August (1986).

  4. Erman, L.D., London, P.E., and Fickas, S.F., The design and an example use of Hearsay-III, Proc. IJCAI-81, pp. 409–415 (1981).

  5. Velthuijsen, H., Lippolt, B.J., and Vonk, J.C., A parallel blackboard architecture, Proc. Third Internat. Expert Systems Conf., pp. 487–493 (1987).

  6. Pang, G.K.H., A blackboard system for the off-line programming of robots, J. Intelligent and Robotic Systems 2, 425–444.

  7. Pang, G.K.H. and Nandy, B., Intelligent scheduling of a group of elevators, Proc. IEEE Internat. Symp. on Intelligent Control., Albany, pp. 144–149 (1989).

  8. Maclean, J., Rudie, K., Zhong, H., and Pang, G.K.H., BESTOOL: A blackboard shell and its application to a traffic control problem, Proc. IEEE Internat. Symp. on Intelligent Control, Virginia, pp. 389–393 (1988).

  9. Meystel, A., Intelligent control in robotics, J. Robotic Systems 5 (4) (August 1988).

  10. Parodi, A.M., A route planning system for an autonomous vehicle, Proc. First Conf. on Artificial Intelligence, pp. 51–56 (1984).

  11. Isik, C. and Meystel, A., Knowledge-based pilot for intelligent mobile autonomous robot, Proc. IEEE Workshop on Intelligent Control, Philadelphia, pp. 124–133 (1985).

  12. Isik, C. and Meystel, A., The structure of a fuzzy production system for autonomous robot control, Proc. Internat. Soc. Optical Engineering, Vol. 635, Applications of Artificial Intelligence III, pp. 545–551 (1986).

  13. Meystel, A., Nested hierarchical intelligent module for automatic generation of control strategies, in U. Rembold and K. Hoermann (eds), NATO Advanced Science Institute Series F: Languages for Sensor-Based Control in Robotics (1986).

  14. Bhatt, R., et al., A real-time pilot for an autonomous robot, Proc. IEEE Internat. Sympos. Intelligent Control, pp. 135–139 (1987).

  15. Crowley, J.L., Coordination of action and perception in a surveillance robot, IEEE Expert, pp. 32–43 (Winter 1987).

  16. Brooks, R.A., A robust layered control system for a mobile robot, IEEE J. of Robotics and Automation, RA, 2, 14–23 (1986).

    Google Scholar 

  17. Durrant-Whyte, H., Integration of distributed sensor information: an application to a robot system coordinator, Proc. IEEE Internat Conf. Systems, Man and Cybernetics Society, Arizona, pp. 415–419 (1985).

  18. Harmon, S.Y. et al. Sensor data fusion through a distributed blackboard Proc. IEEE Internat. Conf. Robotics and Automation, pp. 1449–1454 (1986).

  19. Harmon, S.Y., The ground surveillance robot (GSR): An autonomous vehicle designed to transit unknown terrain, IEEE J. Robotics and Automation, RA 3, 266–279 (1987).

    Google Scholar 

  20. Saridis, G.N. and Stephanou, H.E., A hierarchical approach to the control of a prosthetic arm, IEEE SMC 7, 407–420 (1977).

    Google Scholar 

  21. Saridis, G.N. and Valvanis, K.P., Analytical design of intelligent machines, Automatica, 24, 123–133 (1988).

    Google Scholar 

  22. Saridis, G.N., Analytic formulation of the principle of increasing precision with decreasing intelligence for intelligent machines, Automatica 25 121–126 (1988).

    Google Scholar 

  23. Hoffman, M.A., OHM-TADS: A key element in emergency response, Proc. First Annual Hazardous Materials Management Conf., Philadelphia, pp. 47–51 (1983).

  24. Fire Protection Guide on Hazardous Materials, National Fire Protection Association, Publications Sales Department, Batterymarch Park, Quincy, MA 02269.

  25. Bennett, G.F., Feates, F.S., and Wilder, I., Hazardous Materials Spills Handbook. McGraw-Hill, New York (1982).

    Google Scholar 

  26. Kak, A.C. et al. Experiments in the integration of world knowledge with sensory information for mobile robots, Proc. IEEE Internat. Conf. Robotics and Automation, North Carolina, pp. 734–740 (1987).

  27. Lakin, W.L., Miles, J.A.H., and Byrne, C.D., Intelligent data fusion for naval command and control, in R. Engelmore and T. Morgan (eds.), Blackboard Systems, Addison-Wesley (1988).

  28. Nagao, M., Matsuyama, T., and Mori, H., Structural analysis of complex aerial photograph, Proc. IJCAI-79, pp. 610–616 (1979).

  29. Pearson, E., Boolean free space operators for roving robot incremental environment knowledge acquisition, M.Sc. Thesis, University of Waterloo (1988).

  30. Gentleman, W.M., Realtime applications: Multiprocessors in harmony, NRCC Report No. 30692, Division of Electrical Engineering, National Research Council of Canada (1988).

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Authors and Affiliations

  1. Department of Electrical and Computer Engineering, University of Waterloo, N2L 3G1, Waterloo, Ontario, Canada

    Grantham K. H. Pang

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  1. Grantham K. H. Pang
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Pang, G.K.H. A framework for intelligent control. J Intell Robot Syst 4, 109–127 (1991). https://doi.org/10.1007/BF00440415

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  • DOI: https://doi.org/10.1007/BF00440415

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