Appearance based processes for visual navigation

Abstract

This paper describes the use of appearance based vision for defining visual processes for navigation. A visual processes which transform images to commands and events. A family of visual processes are defined by associating the appearance of a scene from a given viewpoint with the simple trajectories. Appearance is captured as a set of low-resolution images. Energy normalized cross correlation is used to maintain heading, to estimated confidence and to servo control a robot vehicle while following a path. Experimental results are presented which compare results with a single camera, a pair of parallel cameras and a pair of divergent cameras. The most accurate (and robust) navigation is found with a pair of cameras which are slightly divergent.