Non-metric navigation for mobile robot using optical flow

In this paper, we address the problem of non-metric navigation for mobile robot in indoor environment. With pure vision sensors, we tackle the most fundamental problem in autonomous mobile robot navigation - to achieve obstacle avoidance ability in mobile robot. We approach the problem by extracting time-to-contact information using optical flow and motion analysis. Our method is based on flow divergence which contains qualitative depth information of the environment. In addition, we presented a flexible robot heading decision making framework that is able to incorporate higher level navigation task on top of obstacle avoiding behaviour. A state-machine based control scheme is utilized for the coordination of the robot's action defined under a behaviour based design. Through virtual simulation and physical experiments, we demonstrated the effectiveness of our non-metric navigation strategy in unknown environment.