EXPERIMENTAL INVESTIGATION OF MAPPING AND NAVIGATION BASED ON CERTAINTY GRIDS USING SONAR SENSORS

A mapping and navigation system based on certainty grids for an autonomous mobile robot operating in unknown environment is described. The system uses sonar range data to build a map of the robot's surroundings. The range data from sonar sensor are integrated into a probability map that is composed of two dimensional grids which contain the probabilities of being occupied by the objects in the environment. A Bayesian model is used to estimate the uncertainty of the sensor information and to update the existing probability map with new range data. The resulting two dimensional map is used for path planning and navigation. In this paper, the Bayesian updating model which was successfully simulated in our earlier work is implemented on a mobile robot and is shown to be valid in the real world by experiment. This paper also proposes a new path planning method based on weighted distance, which enables the robot to efficiently navigate in an unknown area.