An Experimental Evaluation Of Balance Strategy Based Obstacle Avoidance

Optical flow plays an important role in vision-based navigation. A lot of optical flow based methods have been developed for autonomous robots. In this paper, we evaluate obstacle avoidance methods based on optical flow in synthetic and real-world scenes. Specifically, the balance strategy is chosen and five representative optical flow algorithms are used. The new metrics for obstacle avoidance performance are introduced. Our experiments demonstrate the effectiveness of the balance strategy for obstacle avoidance. Furthermore, some factors contributing to obstacle avoidance ability are studied.