Many researchers are studying ways to create machines that can make their own decisions and act on them. Recently, great advances have been made in intelligent mobile robot technology, advances which will provide autonomous traveling ability to autonomous systems, allowing them not only to surmount stairs but also other obstacles. The autonomous systems are expected to gather knowledge about their environment, construct a symbolic world model of the environment, and use this model in planning and carrying out tasks set them in high-level style. An approach to automatic path planning for self-navigation problems is presented. It is structured as a knowledge-based system and is a method of planning safe paths around circular obstacles in a two-dimensional plane for autonomous systems. The expert system path planner reduces the complexity of the problem and the computer run-time, enabling the agent to achieve a quicker response to its own environment. Also, computer run-time increases very slowly with problem complexity. It is done by: (1) representing the environmental information by sets of facts; (2) guiding the moving object by groups of rules and (3) deriving the result with simple algorithm and fewer calculations. This algorithm is implemented in the expert system environment, and some examples drawn from the system are also demonstrated.
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