An exploration and navigation approach for indoor mobile robots considering sensor's perceptual limitations

Abstract

A method for exploring and navigating autonomously in indoor environments is described. This method merges a local strategy, similar to wall following to keep the robot close to obstacles, within a global search frame, based on a dynamic programming algorithm. We introduce the concept of travel space as a way to map costs to grid cells based on distances to obstacles. This hybrid approach takes advantages of local strategies that consider perceptual limitations of sensors without losing the completeness of a global search. This exploration and navigation method is tested using a simulated and a real mobile robot with promising results.