Topological Maps for Visual Navigation

Abstract

We address the problem of visual-based indoors navigation based on a single camera that provides the required visual feedback information. The usual approach relies on a map to relocate the robot with respect to the environment. Once the robot position and orientation are known, a suitable trajectory is defined according to the mission goals and the structure of the environment. However, one could argue that it should be possible to perform most missions without a precise knowledge of the robot position and orientation. This is indeed the case for many living beings when they navigate in complex environments. We propose to represent the environment as a topological map that is tightly related to the system perceptual and motion capabilities. The map should contain environmental information that can easily be extracted by the system and the mission should be described in terms of a set of available behaviors or primitive actions. We present results that merge visual servoing and appearance based methods. Servoing is used locally when a continuous stream of visual information is available. Appearance based methods offer a means of providing a topological description of the environment, without using odometry information or any absolute localization method. Preliminary tests are presented and discussed.

This research has been partially funded by projects PRAXIS/2/2.1/TPAR/2074/95.