Modeling obstacles and free spaces for a mobile robot using stereo vision with uncertainty

This paper describes a new method of modeling an environment in terms of obstacles and free spaces from a set of 3D segments obtained by stereo vision. Since live stereo vision provides only the position of segments, it is necessary to determine whether a region formed by the segments is an obstacle or a free space. The ambiguities and the uncertainties in the obtained data must be considered in modeling. The final output of the proposed method is a set of possible situations of the environment and their probabilities; each situation consists of the description of obstacles and critical regions between the obstacles. Experimental results for a real scene are described