Abstract
In this paper, theoretical foundations of planning processes are outlined in a form applicable for design and control of autonomous mobile robots. Planning/control is shown to be a unified recursive operation of decision making applied to a nested hierarchy of knowledge representation. The core of the theory is based upon methods developed in the areas of Post-production systems, theory of coding, and the team theory of decentralized stochastic control. A class of autonomous control systems for robots is defined, and a problem of information representation is addressed for this class. A phenomenon of nesting is analyzed and the minimum c-entropy rule is determined for arranging efficient design and control procedures for systems of intelligent control. A concept of nested hierarchical knowledge-based controller is employed in this paper which enables minimum-time control using nested dynamic programming. An application of this concept is unfolded for a system of knowledge-based control of an autonomous mobile robot. Key words: Autonomous Control Systems, Decision Making, Production Systems, Decentralized Stochastic Control, Dynamic Programming, Hierarchical Control, Knowledge Based Controllers, E-entropy, Planning, Navigation, Guidance, Prediction, Contingencies, Mobile Robots.
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