Document image analysis by a mobile robot for autonomous indoor navigation

This paper proposes the analysis of a paper-based floor plan of a building for reference purposes in the navigation task of a mobile robot. The novelty of this approach lies in the combination of this information extracted from the document image in real time just prior to real world exploration with dynamic visual perception. An artificial neural system integrates both sets of information by having the robot recognize navigation signs from the floor plan and then look for them in the expected sequence in the environment. Thereafter, while determining and executing appropriate movements as a response to the environment, the robot links and learns to associate the undertaken movements to the respective signs. The analysis of the floor plan involves a detailed process permitting the robot to extract the required information in real time. This process is elaborated in this paper, along with experiments with the robot using the proposed architecture in a simple navigation scenario, hence proving the feasibility of the approach.