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Behaviour rule selection using alpha-level FIS for mobile robot navigation during multiple rule conflicts in complex environments

A common problem in robot navigation is behaviour rule selection when more than one action of the same type is available. Here action selection or decision-making procedure incorporating α-level fuzzy logic is discussed and used for selecting an appropriate action during mobile robot navigation. In the present approach, the operational strategies of the human expert driver are transferred via fuzzy logic to the robot navigation in the form of optimising behaviour rules without decreasing the input space and resolved the conflicts similar to human thinking. This paper presents the mathematical aspects of resolving conflicts when more than one context rule of the same kind is in action. Simulation results are presented based on the real life situation. The techniques presented in this paper are validated by conducting real world experiments using Khepera miniature Robot.