Image based autonomous navigation with fuzzy logic control

This work presents a computational model of an adaptive image based autonomous navigation system using fuzzy logic control. A mobile robot moves in an environment from which images provide the necessary guidance information. The fuzzy logic system determines the directions to be followed for each point on the road. The system shows autonomy in adaptively navigating in the environment with image feedback, and automatically correcting its trajectory based on the information from the images. This is analog to human behavior while navigating in an environment. Experiments were conducted in an indoor environment in which simple computer vision techniques were applied to extract features of the road, and to feed the fuzzy logic system with linguistic variables that carried information about the directions of the road. The system decides the direction to follow from the actual position. The rules were constructed by considering a common sense driver model. The adequacy of the model for robot image based navigation is shown