Visually-guided obstacle avoidance in unstructured environments

Abstract

This paper presents an autonomous vision-based obstacle avoidance system. The system consists of three independent vision modules for obstacle detection, each of which is computationally simple and uses a different criterion for detection purposes. These criteria are based on brightness gradients, RGB (red, green, blue) color, and HSV (hue, saturation, value) color, respectively. Selection of which modules are used to command the robot proceeds exclusively from the outputs of the modules themselves. The system is implemented on a small monocular mobile robot and uses very lour resolution images. It has been tested for over 200 hours in diverse environments.