A view-based outdoor navigation using object recognition robust to changes of weather and seasons

This paper describes a view-based outdoor navigation method. In the method, a user first guides a robot along a route. During this guided movement, the robot learns a sequence of images and a rough geometry of the route. The robot then moves autonomously along the route with localizing itself based on the comparison between the learned images and input images. Since appearances of objects in images may vary much according to changes of seasons and weather in outdoor scenes, a simple image comparison does not work. We, therefore, propose a comparison method in which the robot first recognizes objects in images using object models which allow for appearance variations, and then compares recognition results of learned and input images. We also developed a method which automatically selects key images used for the comparison from an image sequence. Successful autonomous navigation experiments in our campus under various conditions show the feasibility of the method.