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Conf. on Control, Automation, Robotics and Computer Vision, Singapore, 1-376, 1996. [33] Quillian, M. , MIT Press, Cambridge, MA, pp. 227270, 1968. [34] Rajendra, C. , “An efficient heuristic approach to the scheduling of jobs in a flowshop,” European Journal of Operational Research, vol. 61, pp. 318-325, 1991. [35] Rich, E. , Artificial Intelligence, McGraw-Hill, New York, 1996. [36] Russel, S. , Artificial Intelligence: A Modern Approach, Prentice-Hall, Englewood Cliffs, NJ, 1995. , Treloar, N.

The interpretation process, on the other hand, requires knowledge-based computation. Navigational Planning for Mobile Robots: Mobile robots, sometimes called automated guided vehicles (AGV), are a challenging area of research, where AI finds extensive applications. A mobile robot generally has one or more camera or ultrasonic sensors, which help in identifying the obstacles on its trajectory. The navigational planning problem persists in both static and dynamic environments. In a static environment, the position of obstacles is fixed, while in a dynamic environment the obstacles may move at arbitrary directions with varying speeds, lower than the maximum speed of the robot.

Schwecke, E. , Uncertainty and Vagueness in Knowledge Based Systems, Springer-Verlag, Berlin, 1991. , The Age of Intelligent Machines, MIT Press, Cambridge, 1990. [18] Luger, G. F. and Stubblefield, W. , Artificial Intelligence: Structures and Strategies for Complex Problem Solving, Benjamin/Cummings, Menlo Park, CA, 1993. [19] Mamdani, E. , Application of fuzzy set theory to control systems, in Fuzzy Automata and Decision Processes, Gupta, M. , Saridies, G. N. and Gaines, B. , Oxford University Press, Amsterdam, New York, pp.

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