Enhanced Fast Vision-Based Obstacle Avoidance Algorithm

Abstract

In this paper, we propose an extended object size detector to identify the frontal obstacle approaching during quadcopters navigation. This algorithm has a low computation complexity and robustness to the background noise. Experimental results, performed in the GAZEBO simulator, confirm the accuracy and the high performance of the proposed approach.